# Hermes Atlas — Full Context Bundle > Complete content of hermesatlas.com as of 2026-10-26. Concatenated from guide pages, ecosystem overview, the quarterly report, and project summaries. Canonical URLs preserved throughout. This file is the companion to https://hermesatlas.com/llms.txt (the concise index). --- # ECOSYSTEM # Hermes Atlas > The community-curated map of every tool, skill, plugin, and integration for [Hermes Agent](https://github.com/NousResearch/hermes-agent) by [Nous Research](https://nousresearch.com). Hermes Agent is an autonomous, self-improving AI agent with persistent memory, auto-generated skills, and multi-platform deployment — MIT licensed, 57k+ stars. > > **Live site:** [hermesatlas.com](https://hermesatlas.com) · **Last updated:** 2026-04-11 · **Hermes version:** 0.8.0 --- ## How to Read This Map Each entry includes a one-line description, link, star count, and maturity indicator: - **Production** — Stable, actively maintained, safe to depend on - **Beta** — Functional but evolving, expect breaking changes - **Experimental** — Early-stage, interesting concept, use with caution Repos are filtered for quality: we exclude unfinished projects, personal experiments, 0-star repos, and anything that doesn't add clear value to the Hermes ecosystem. Repos marked with `official` are by Nous Research. --- ## Table of Contents 1. [Core & Official](#core--official) 2. [Workspaces & GUIs](#workspaces--guis) 3. [Skills & Skill Registries](#skills--skill-registries) 4. [Plugins & Extensions](#plugins--extensions) 5. [Memory & Context](#memory--context) 6. [Multi-Agent & Orchestration](#multi-agent--orchestration) 7. [Deployment & Infrastructure](#deployment--infrastructure) 8. [Integrations & Bridges](#integrations--bridges) 9. [Developer Tools & Utilities](#developer-tools--utilities) 10. [Domain Applications](#domain-applications) 11. [Guides & Documentation](#guides--documentation) 12. [Ecosystem Resources](#ecosystem-resources) --- ## Core & Official The foundational repos maintained by Nous Research. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [NousResearch/hermes-agent](https://github.com/NousResearch/hermes-agent) `official` | The core agent — self-improving AI with persistent memory, 47 tools, 14 messaging platforms, and 6 execution backends | 43,724 | Production | | [NousResearch/hermes-agent-self-evolution](https://github.com/NousResearch/hermes-agent-self-evolution) `official` | Evolutionary self-improvement for Hermes — optimizes skills, prompts, and code using DSPy + GEPA | 778 | Beta | | [NousResearch/hermes-paperclip-adapter](https://github.com/NousResearch/hermes-paperclip-adapter) `official` | Run Hermes as a managed employee in Paperclip company systems | 663 | Beta | | [NousResearch/autonovel](https://github.com/NousResearch/autonovel) `official` | Autonomous novel-writing pipeline generating 100k+ word manuscripts | 401 | Beta | | [NousResearch/Hermes-Function-Calling](https://github.com/NousResearch/Hermes-Function-Calling) `official` | Function calling examples and training data for Hermes LLM models | 1,249 | Production | --- ## Workspaces & GUIs Web-based and desktop interfaces that wrap Hermes with visual UIs. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [outsourc-e/hermes-workspace](https://github.com/outsourc-e/hermes-workspace) | Native web workspace — chat, terminal, memory browser, skills manager, and inspector panel | 830 | Beta | | [Euraika-Labs/pan-ui](https://github.com/Euraika-Labs/pan-ui) | Self-hosted AI workspace for Hermes with chat, skills, extensions, memory, and runtime controls | 26 | Experimental | | [fathah/hermes-desktop](https://github.com/fathah/hermes-desktop) | Desktop application wrapper for Hermes Agent | 65 | Beta | | [sanchomuzax/hermes-webui](https://github.com/sanchomuzax/hermes-webui) | Process monitoring and configuration dashboard for Hermes | 57 | Beta | --- ## Skills & Skill Registries Skills are on-demand knowledge documents following the [agentskills.io](https://agentskills.io) open standard. These repos provide ready-made skills or platforms for discovering them. ### Skill Libraries | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [mukul975/Anthropic-Cybersecurity-Skills](https://github.com/mukul975/Anthropic-Cybersecurity-Skills) | 754 structured cybersecurity skills mapped to MITRE ATT&CK, NIST CSF 2.0, ATLAS, D3FEND & NIST AI RMF | 4,132 | Production | | [conorbronsdon/avoid-ai-writing](https://github.com/conorbronsdon/avoid-ai-writing) | Audits and rewrites content to eliminate detectable AI writing patterns | 759 | Production | | [wondelai/skills](https://github.com/wondelai/skills) | Cross-platform skills library for Claude Code and agentskills.io-compatible agents | 480 | Production | | [smartcontractkit/chainlink-agent-skills](https://github.com/smartcontractkit/chainlink-agent-skills) | Oracle network and smart contract interaction skills (agentskills.io spec) | 85 | Beta | | [black-forest-labs/skills](https://github.com/black-forest-labs/skills) | Official FLUX image generation skills — prompting guidelines and API integration | 44 | Production | | [Agents365-ai/drawio-skill](https://github.com/Agents365-ai/drawio-skill) | Generate draw.io diagrams from natural language descriptions | 131 | Beta | | [tlehman/litprog-skill](https://github.com/tlehman/litprog-skill) | Literate programming skill — weave code and documentation across agents | 81 | Beta | | [Romanescu11/hermes-skill-factory](https://github.com/Romanescu11/hermes-skill-factory) | Meta-skill plugin that watches workflows and auto-generates reusable skills | 34 | Beta | | [tiann/execplan-skill](https://github.com/tiann/execplan-skill) | Complex multi-step task execution with checkpoints and recovery | — | Beta | | [ReinaMacCredy/maestro](https://github.com/ReinaMacCredy/maestro) | Multi-step skill orchestration and chaining | — | Beta | | [esaradev/icarus-plugin](https://github.com/esaradev/icarus-plugin) | Self-memory and replacement models — remember your work, train your replacement | 51 | Beta | | [DougTrajano/pydantic-ai-skills](https://github.com/DougTrajano/pydantic-ai-skills) | Type-safe schema validation for agentskills.io skills | — | Beta | | [armelhbobdad/bmad-module-skill-forge](https://github.com/armelhbobdad/bmad-module-skill-forge) | Converts existing repos into agentskills.io format | — | Beta | | [cablate/Agentic-MCP-Skill](https://github.com/cablate/Agentic-MCP-Skill) | MCP client with skills validation layer | — | Beta | | [PederHP/skillsdotnet](https://github.com/PederHP/skillsdotnet) | C# / .NET implementation of the agentskills.io standard | — | Experimental | ### Skill Registries & Discovery | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [chigwell/skilldock.io](https://github.com/chigwell/skilldock.io) | Registry of reusable AI skills based on AgentSkills specification | 50 | Production | | [amanning3390/hermeshub](https://github.com/amanning3390/hermeshub) | Community skill browsing, search, and one-click installation | — | Beta | --- ## Plugins & Extensions Plugins extend Hermes with new tools, data sources, or behaviors at the framework level. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [42-evey/hermes-plugins](https://github.com/42-evey/hermes-plugins) | Goal management, inter-agent bridge, model selection, and cost control plugins | 16 | Beta | | [42-evey/evey-bridge-plugin](https://github.com/42-evey/evey-bridge-plugin) | Claude Code ↔ Hermes context sharing bridge | — | Beta | | [robbyczgw-cla/hermes-web-search-plus](https://github.com/robbyczgw-cla/hermes-web-search-plus) | Multi-provider web search routing (fallback across search APIs) | — | Beta | | [FahrenheitResearch/hermes-weather-plugin](https://github.com/FahrenheitResearch/hermes-weather-plugin) | Professional weather data with NWS imagery and forecasts | — | Beta | | [nativ3ai/hermes-payguard](https://github.com/nativ3ai/hermes-payguard) | Safe USDC and x402 payment handling for agents | — | Experimental | --- ## Memory & Context Extensions to Hermes's built-in memory system — external providers, context engines, and recall tools. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [vectorize-io/hindsight](https://github.com/vectorize-io/hindsight) | Long-term memory provider with retain/recall/reflect workflows | 8,362 | Production | | [elkimek/honcho-self-hosted](https://github.com/elkimek/honcho-self-hosted) | Self-hosted Honcho memory backend for cross-session persistence | 126 | Beta | | [yoloshii/ClawMem](https://github.com/yoloshii/ClawMem) | On-device memory and context engine for agents | 86 | Beta | | [plur-ai/plur](https://github.com/plur-ai/plur) | Shared memory layer with open engram YAML format for multi-agent systems | 31 | Beta | | [amanning3390/flowstate-qmd](https://github.com/amanning3390/flowstate-qmd) | Anticipatory memory with RAG and vector search | — | Experimental | | [greyhaven-ai/autocontext](https://github.com/greyhaven-ai/autocontext) | Recursive self-improving context harness — helps agents succeed on complex tasks | 711 | Beta | --- ## Multi-Agent & Orchestration Frameworks for running multiple Hermes agents or coordinating agent swarms. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [builderz-labs/mission-control](https://github.com/builderz-labs/mission-control) | Self-hosted AI agent orchestration — dispatch tasks, run multi-agent workflows, monitor spend | 3,875 | Beta | | [swarmclawai/swarmclaw](https://github.com/swarmclawai/swarmclaw) | Build autonomous AI agent swarms with orchestration, skills, and multiple model providers | 285 | Beta | | [1ilkhamov/opencode-hermes-multiagent](https://github.com/1ilkhamov/opencode-hermes-multiagent) | 17 specialized agents with structured communication protocols | — | Beta | | [Abruptive/Ankh.md](https://github.com/Abruptive/Ankh.md) | TAW Agent × Hermes swarm framework for multi-agent collaboration | 25 | Experimental | | [runtimenoteslabs/gladiator](https://github.com/runtimenoteslabs/gladiator) | Autonomous AI companies competing for GitHub stars — agent-vs-agent arena | 29 | Experimental | --- ## Deployment & Infrastructure Docker images, deployment templates, and infrastructure tooling for running Hermes in production. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [xmbshwll/hermes-agent-docker](https://github.com/xmbshwll/hermes-agent-docker) | Minimal Docker sandbox image for Hermes | — | Beta | | [0xrsydn/nix-hermes-agent](https://github.com/0xrsydn/nix-hermes-agent) | Nix package and NixOS module for reproducible Hermes deployment | — | Beta | | [numtide/llm-agents.nix](https://github.com/numtide/llm-agents.nix) | Nix packages for AI coding agents including Hermes | 967 | Production | | [JackTheGit/hermes-autonomous-server](https://github.com/JackTheGit/hermes-autonomous-server) | Headless systemd deployment for always-on Hermes | — | Experimental | | [TheAiSingularity/hermesclaw](https://github.com/TheAiSingularity/hermesclaw) | Hermes Agent sandboxed with hardware-level enforcement | 16 | Experimental | --- ## Integrations & Bridges Connect Hermes to external platforms, services, and ecosystems. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [teknium1/hermes-miniverse](https://github.com/teknium1/hermes-miniverse) | Bridge Hermes to Miniverse pixel worlds — agent embodiment in virtual environments | 8 | Experimental | | [gizdusum/hermes-blockchain-oracle](https://github.com/gizdusum/hermes-blockchain-oracle) | Solana on-chain analytics MCP server for Hermes | — | Experimental | | [Ridwannurudeen/hermes-council](https://github.com/Ridwannurudeen/hermes-council) | Adversarial multi-perspective MCP server for decision-making | — | Experimental | --- ## Developer Tools & Utilities Tools that make developing with, debugging, or optimizing Hermes easier. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [junhoyeo/tokscale](https://github.com/junhoyeo/tokscale) | Token usage tracker for Claude Code, OpenClaw, Hermes, and other agents | 1,690 | Production | | [joeynyc/hermes-skins](https://github.com/joeynyc/hermes-skins) | Community CLI skins and themes for Hermes terminal UI | 76 | Beta | | [hermes-labs-ai/lintlang](https://github.com/hermes-labs-ai/lintlang) | Deterministic linting for agent instructions, tools, and skills; native Hermes Agent `pre_verify` plugin | — | Beta | | [0xNyk/openclaw-to-hermes](https://github.com/0xNyk/openclaw-to-hermes) | Migration tool from OpenClaw to Hermes Agent | 21 | Beta | | [unmodeled-tyler/vessel-browser](https://github.com/unmodeled-tyler/vessel-browser) | AI-native browser built for autonomous agent control via MCP | 44 | Experimental | | [42-evey/evey-setup](https://github.com/42-evey/evey-setup) | One-command Hermes stack setup with 29 pre-configured plugins | — | Beta | | [aivrar/portable-hermes-agent](https://github.com/aivrar/portable-hermes-agent) | Windows desktop app bundling Hermes with 100 tools | — | Beta | | [AlexAI-MCP/hermes-CCC](https://github.com/AlexAI-MCP/hermes-CCC) | Hermes Agent ported to Claude Code Channel — 46 native skills, no OAuth, no external process | 56 | Beta | | [howdymary/hermes-agent-metaharness](https://github.com/howdymary/hermes-agent-metaharness) | Meta-harness implementation for Hermes Agent orchestration | 46 | Beta | --- ## Domain Applications Purpose-built agents and workflows powered by Hermes for specific use cases. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [ucsandman/DashClaw](https://github.com/ucsandman/DashClaw) | Decision infrastructure with guard policies and risk assessment for agents | 204 | Beta | | [bigph00t/hermescraft](https://github.com/bigph00t/hermescraft) | Minecraft companion agent with persistent memory and world awareness | — | Beta | | [rodmarkun/anihermes](https://github.com/rodmarkun/anihermes) | Anime media server with natural language interface powered by Hermes | — | Beta | | [Christabel337/job-scout-agent](https://github.com/Christabel337/job-scout-agent) | Autonomous job hunting — scans listings, writes cover letters, tracks applications | — | Beta | | [JackTheGit/hermes-ai-infrastructure-monitoring-toolkit](https://github.com/JackTheGit/hermes-ai-infrastructure-monitoring-toolkit) | Infrastructure monitoring, alerting, and cost forecasting | — | Beta | | [hxsteric/mercury](https://github.com/hxsteric/mercury) | Multi-chain blockchain cash flow analyzer | — | Beta | | [Lethe044/hermes-incident-commander](https://github.com/Lethe044/hermes-incident-commander) | Production incident detection and self-healing workflows | — | Beta | | [bryercowan/hermes-embodied](https://github.com/bryercowan/hermes-embodied) | Self-improving robotics via VLA model fine-tuning | — | Experimental | --- ## Guides & Documentation Community-created documentation, tutorials, and setup guides. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [alchaincyf/hermes-agent-orange-book](https://github.com/alchaincyf/hermes-agent-orange-book) | Hermes Agent practical guide — Orange Book series (Chinese) | 315 | Beta | | [OnlyTerp/hermes-optimization-guide](https://github.com/OnlyTerp/hermes-optimization-guide) | Performance optimization guide for Hermes deployments | 51 | Beta | | [metantonio/hermes-wsl-ubuntu](https://github.com/metantonio/hermes-wsl-ubuntu) | Step-by-step WSL2 Ubuntu setup guide for Windows users | — | Production | | [mudrii/hermes-agent-docs](https://github.com/mudrii/hermes-agent-docs) | Community documentation covering deployment patterns and v0.2.0+ workflows | — | Beta | | [martymcenroe/HermesWiki](https://github.com/martymcenroe/HermesWiki) | Community wiki with deployment patterns and recipes | — | Beta | --- ## Ecosystem Resources Meta-resources for navigating the Hermes ecosystem. | Resource | Description | Link | |:---------|:------------|:-----| | Official Documentation | Comprehensive setup, configuration, and API reference | [hermes-agent.nousresearch.com/docs](https://hermes-agent.nousresearch.com/docs) | | Nous Research Discord | Community support and discussion | [discord.gg/NousResearch](https://discord.gg/NousResearch) | | awesome-hermes-agent | Curated community list of skills, tools, and integrations (898 stars) | [github.com/0xNyk/awesome-hermes-agent](https://github.com/0xNyk/awesome-hermes-agent) | | agentskills.io | Open standard for cross-platform agent skills | [agentskills.io](https://agentskills.io) | | Nous Portal | Official inference endpoint and subscription service | [portal.nousresearch.com](https://portal.nousresearch.com) | | Skills Hub (built-in) | Browse and install skills via `hermes skills browse` | CLI: `hermes skills browse` | | skilldock.io | Third-party registry of reusable AI skills | [github.com/chigwell/skilldock.io](https://github.com/chigwell/skilldock.io) | --- ## Ecosystem Statistics | Metric | Count | |:-------|------:| | Core repos (Nous Research) | 6 | | Community repos (quality-filtered) | 75+ | | Total ecosystem stars | 60,000+ | | Skill libraries | 15+ | | Plugins | 7+ | | Deployment templates | 7 | | Messaging platforms supported | 14 | | LLM providers supported | 18+ | | Terminal backends | 6 | | Built-in tools | 47 | --- ## Forks & Derivatives Notable forks that add significant functionality beyond the base Hermes agent. | Repository | Description | Stars | Maturity | |:-----------|:------------|------:|:---------| | [nativ3ai/hermes-agent-camel](https://github.com/nativ3ai/hermes-agent-camel) | Hermes with integrated CaMeL trust boundaries for safer autonomous execution | 12 | Beta | | [kaminocorp/hermes-alpha](https://github.com/kaminocorp/hermes-alpha) | Cloud-deployed Hermes with pre-configured templates and managed infrastructure | — | Beta | | [beardthelion/hermes-skill-distillation](https://github.com/beardthelion/hermes-skill-distillation) | Fine-tuning trajectory generation from Hermes skill executions | — | Experimental | --- ## Security Notes All community repos with 25+ stars were reviewed for obfuscated code, credential harvesting, typosquatting, supply chain attacks, crypto mining, and excessive permissions. **No repos were found to be malicious.** Full report: [`repos/security-review.md`](repos/security-review.md). Five repos received WARN status (not for malicious behavior, but for patterns requiring user caution): | Repo | Concern | Recommendation | |:-----|:--------|:---------------| | swarmclawai/swarmclaw | README could not be fully audited | Inspect source before use | | AlexAI-MCP/hermes-CCC | PowerShell `install.ps1` + curl-pipe-bash installer | Inspect install scripts before running | | unmodeled-tyler/vessel-browser | curl-pipe-bash installer with broad scope | Download and inspect `install.sh` first | | runtimenoteslabs/gladiator | Hardcoded dev DB creds, 0.0.0.0 binding without auth | Not recommended for production use without hardening | | joeynyc/hermes-skins | README could not be fully audited | Low risk (visual themes only), but inspect before use | **General advice:** For any repo with a `curl ... | bash` installer, download the script first and review it before executing. --- ## About This Map This ecosystem map was compiled on 2026-04-08 by researching the [Hermes Agent GitHub repository](https://github.com/NousResearch/hermes-agent), its [official documentation](https://hermes-agent.nousresearch.com/docs), the [awesome-hermes-agent](https://github.com/0xNyk/awesome-hermes-agent) curated list, and comprehensive GitHub API searches across topics, names, and README references. **Filtering criteria:** - Must be specifically built for or integrated with Hermes Agent - Created after July 22, 2025 (Hermes repo creation date) — except pre-existing tools that later added Hermes support - Not a personal pet project or homework assignment - Shows genuine effort and adds value to the ecosystem - Excludes direct forks without meaningful changes - Security-reviewed for obvious red flags **Contributing:** Found a repo that should be listed? The [awesome-hermes-agent](https://github.com/0xNyk/awesome-hermes-agent) list accepts community PRs. --- # The Hermes Handbook (/guide/) Canonical URL: https://hermesatlas.com/guide/ # Hermes Agent: The Complete Beginner's Guide (Oct 2026) By [Kevin Simback](https://x.com/ksimback) · Hermes Atlas maintainer · Updated 2026-04-20 > Based on 100+ ecosystem projects reviewed, 33 research sources, and the live GitHub repo. We update this handbook monthly. --- ## Table of contents 1. [What Hermes Agent actually is](#1-what-hermes-agent-actually-is) 2. [Who Hermes is for](#2-who-hermes-is-for) 3. [How it's different (vs Claude Code, Cursor, OpenClaw)](#3-how-its-different) 4. [Install in 2 minutes](#4-install-in-2-minutes) 5. [Pick your model (the first-weekend mistake)](#5-pick-your-model) 6. [Your first workflow](#6-your-first-workflow) 7. [The learning loop](#7-the-learning-loop) 8. [Essential skills to install first](#8-essential-skills-to-install-first) 9. [Where to go next](#9-where-to-go-next) 10. [FAQ](#10-faq) --- ## 1. What Hermes Agent actually is **Hermes Agent is an open-source AI agent by [Nous Research](https://nousresearch.com) that runs on your own machine or a cheap VPS, remembers what it learns across sessions, and writes its own reusable skills as it works. It talks to you through a CLI, Telegram, Discord, email, and many other messaging providers. It hit 257,151 GitHub stars (as of 2026-10-26), and it's the fastest-growing open-source agent of 2026.** ### The 30-second version You install Hermes with one curl command. You pick a model provider (many popular options) and a model (Claude, GPT-5.4, GLM-5.1, MiniMax, or even a local Ollama model). You give it a job — "summarize my GitHub notifications every morning at 8am," or "help me debug this Python script," or "watch this website and ping me on Telegram when the price drops." It runs. It learns. A week later, the same job produces tighter output because Hermes has been quietly writing skills — little markdown files that capture what worked — and pulling them into future runs. That's the whole product. Install, assign tasks, and let it compound. ### The 2-minute version Most AI tools are stateless: you open a chat, ask a question, close the tab, and the next session starts from zero. Hermes inverts that. It lives on a personal computer or virtual private server. It has persistent memory. It creates skills — procedures it can reuse — every time it figures something out. And it reaches you through whatever channel you prefer: a terminal, a Telegram bot, a scheduled cron job, a webhook. The big architectural bet is **Harness Engineering**: Nous believes the real unlock in 2026 isn't a smarter model, it's a smarter wrapper around the model. So Hermes invests heavily in five layers around the LLM — instructions, constraints, feedback, memory, orchestration — and lets you swap the model itself. Frontier today, local tomorrow, something else next year. You'll hear people call this "the agent that grows with you." That's Nous's tagline and it's also a useful mental model: on day one Hermes is a generic assistant. On day thirty it's *your* assistant, with thirty days of learned preferences baked in. ### Preview: the learning loop Every few tool calls, Hermes pauses and asks itself: *what just happened, what worked, what failed, should this become a skill?* When the answer is yes, it writes a skill file to `~/.hermes/skills/` and uses it going forward. These skills are plain markdown. You can read them, edit them, or delete the ones it got wrong. This is the single feature that matters most and the one we'll unpack in [chapter 7](#7-the-learning-loop). --- ## 2. Who Hermes is for Hermes attracts three kinds of people. Figure out which one you are and the rest of the handbook makes more sense. ### The CLI coder You live in a terminal. You already use Claude Code or Cursor for in-editor coding. You want an agent that sits *outside* your editor — something you can ask to "audit the repo for dead code" or "write a migration plan for our 0.9 → 0.10 upgrade" without leaving the CLI. **What you'll use first:** the `hermes` CLI, skills, memory. **Ignore for now:** Telegram, cron, multi-agent. ### The automation operator You don't necessarily code. You want an agent that does recurring jobs — summarize news, watch markets, generate reports, triage your inbox — while you sleep. You'll host Hermes on a Mac Mini or $5 VPS and wire it to whatever channels you use. **What you'll use first:** cron, messaging gateways, memory. **Ignore for now:** code execution, multi-agent. ### The Telegram-bot operator You want an always-on agent you can message from your phone. Travel, meetings, gym — doesn't matter, you ping Hermes and it responds. The Telegram integration is the killer feature here. **What you'll use first:** the messaging gateway, voice, skills. **Ignore for now:** local CLI usage. ### Which one are you? | If you want to... | Start with... | Skip (for now) | |---|---|---| | Write better code from the terminal | CLI + skills | Telegram, cron | | Automate recurring jobs | Cron + gateway | Code execution | | Chat with an agent from your phone | Telegram + voice | CLI workflows | All three can coexist later. Pick one for the first week. --- ## 3. How it's different You probably already use Claude Code, Cursor, or OpenClaw. Where does Hermes fit? ### The one-liner **Claude Code is an in-repo coding agent. Cursor is an in-editor pair programmer. OpenClaw is a configuration-driven task runner. Hermes is a self-improving autonomous agent that lives outside all of them.** Most power users run two or three of these together, not one. ### Comparison at a glance | Feature | Claude Code | Cursor | OpenClaw | **Hermes Agent** | |---|---|---|---|---| | Primary surface | CLI in a repo | IDE | CLI + configs | CLI + chat + cron + Telegram | | Persistent memory | Session-scoped | Project-scoped | Config-file based | **Cross-session, bounded (MEMORY.md, USER.md)** | | Learning | None | None | None | **Auto-generates skills after repeated patterns** | | Channels | Terminal | Editor | Terminal | **Terminal, Telegram, Discord, email, webhooks** | | Scheduled jobs | No | No | No | **Built-in cron** | | Self-improvement | No | No | No | **Yes, via skills + memory** | | Model lock-in | Anthropic | Multiple | Multiple | **18+ providers, swap with one command** | | Best for | Coding in a repo | Writing code inline | Running shell workflows | **Long-running autonomous tasks that compound** | ### When to pick which - **Pick Claude Code** when you're inside a repo and want the agent to read code, edit code, run tests, commit. It's a coding specialist. - **Pick Cursor** when you want AI completions and fixes inside your editor in real time. - **Pick OpenClaw** when you want to declaratively configure a task runner with composable commands. - **Pick Hermes** when you want an agent that (a) lives beyond any single session, (b) talks to you from any channel, (c) gets better at your recurring work over time. ### You probably want to run two Most of the community runs Hermes *alongside* Claude Code. Claude Code for inside-the-repo coding. Hermes for everything else: daily briefings, monitoring, automation, multi-repo research, cross-channel coordination. They don't compete; they stack. If you're migrating from OpenClaw, Nous ships a migration tool that ports your configs automatically. That friction is near zero. Deeper comparison: see the **[Hermes vs Claude Code full breakdown →](/guide/vs-claude-code/)** --- ## 4. Install in 2 minutes Installing Hermes is one curl command followed by two small config steps. If everything works, you're done in under two minutes. If it breaks, it's almost always one of three things, all covered below. ### Prerequisites - **macOS, Linux, Windows, Android (Termux).** Linux, macOS, and WSL2 are first-class. Native Windows works via an early-beta PowerShell installer. Termux on Android works via a curated install path. - **A terminal.** Any shell works — bash, zsh, fish, PowerShell. - **An API key or a local model.** If you don't have a model provider or want to set up a new one for your agent, a great place to start is the [Nous Portal](https://portal.nousresearch.com) — otherwise just grab an API key from your model provider, or a local Ollama/LM Studio install. You can always swap model providers later. - **~200 MB of disk** for the install plus whatever you use for memory and skills. ### Install **macOS, Linux, WSL2, Termux:** ```bash curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash ``` **Native Windows (PowerShell, early beta):** ```powershell irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex ``` The installer sets up `uv`, Python 3.11, Node.js, `ripgrep`, `ffmpeg`, the venv, and the `hermes` command. On Linux/macOS it drops the binary under `~/.hermes/` and symlinks `~/.local/bin/hermes`. On Windows it installs to `%LOCALAPPDATA%\hermes` with a bundled portable Git Bash. The installer prints everything it does — no hidden steps. ### First run ```bash hermes ``` Hermes walks you through provider setup interactively on the first run. Paste an API key when prompted, or point it at a local model. Confirm with `hermes model` to see what's configured. ### Verify ```bash hermes doctor ``` Prints a health report. Green across the board means you're ready. Red lines usually map to one of the pitfalls below. ### Three common pitfalls 1. **"Command not found: hermes"** → your shell didn't pick up the new PATH. Open a fresh terminal or run `source ~/.bashrc` (or `~/.zshrc`). 2. **"Provider error: invalid key"** → the key you pasted has a trailing space or is for the wrong provider. Re-run `hermes model` and paste carefully. 3. **Windows: "bad interpreter"** → you ran the Linux `curl ... | bash` command in PowerShell or cmd. Either install WSL2 (`wsl --install` in PowerShell) and rerun from inside WSL, or use the native PowerShell installer instead (`irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex`). Everything else is rare. If `hermes doctor` shows a problem it doesn't explain, open an issue on [the Hermes repo](https://github.com/NousResearch/hermes-agent) — the Nous team triages quickly. --- ## 5. Pick your model **This is where most first-time setups silently fail.** If Hermes feels broken, dumb, or slow in your first session, the model is almost always the reason — not Hermes. Spend two minutes here and save yourself a weekend. ### The first-weekend mistake Hermes delegates heavily to the model. Tool calling, planning, skill writing — it's all the model's job. Small or older models can't reliably call tools, so they get stuck in loops or produce garbage. **Small local models (the 8B-and-under class) and older releases are almost always the wrong default.** They run fine for chat, not for agent workflows. The community consensus: use a frontier model for real work; use a local model only for experimentation. ### Cost and capability at a glance | Model | Price tier | Tool calling | Speed | Best for | |---|---|---|---|---| | Claude Sonnet / Opus | $$$ | Excellent | Fast | Production agent workflows | | GPT-5 | $$$ | Excellent | Fast | Production, OpenAI stack users | | z.AI GLM-5 | $ | Excellent | Fast | Best-value frontier | | MiniMax M2.7 | $$ | Excellent | Fast | Excellent value | | DeepSeek | $ | Good | Fast | Cost-optimized workflows | | Nous Portal (subscription) | $ (flat) | Excellent | Fast | Predictable monthly cost | | Ollama + Gemma 4 26B / Qwen 3.5 | Free (local) | Good | Depends on GPU | Offline coding, privacy-sensitive work | | Ollama + small models (8B and under) | Free (local) | **Poor** | Depends on GPU | Chat-only; don't use for agent work | ### When local is fine, when it isn't - **Local is fine when:** you're drafting code snippets, chatting, or running single-shot summarization. Gemma 4 26B via Ollama is the community's current pick for local experiments; Qwen 3.5 (via Ollama or LM Studio) is the popular alternative. One trap: Hermes needs a 64K-token context window and Ollama defaults to 4K — raise it or tool calls break silently. - **Local isn't fine when:** you want multi-step tool calls (watch a site, call an API, summarize, post to Telegram). You'll hit loops, timeouts, and bad tool arguments. Switch to a frontier API. ### The easy button: Nous Portal If you don't want to manage API keys across providers, Nous Portal is a single subscription that covers Claude, GPT, GLM, MiniMax, Nous's own models, and many more via one auth. Sign in with OAuth from the CLI. You pay one flat monthly fee and stop thinking about which key is which. Most people end up here eventually. --- ## 6. Your first workflow Don't try to build three things at once. Pick one of the following examples and ship it today. Each takes 10–30 minutes and teaches you a different half of Hermes. ### Example 1 — Coding assistant on your laptop ```bash cd ~/projects/my-repo hermes > audit this repo for dead code, imports that aren't used, and commented-out blocks older than 6 months. Produce a markdown report. ``` What you'll notice: Hermes reads files, runs greps, and writes the report to `./hermes-output/` by default. The second time you ask the same kind of question, it's faster — because it wrote a skill called `repo-audit` on run one. **Why this is a good first workflow:** zero infrastructure, tangible output, and you'll see the skill system kick in inside one afternoon. ### Example 2 — Telegram bot on a $5 VPS On any cheap Linux VPS (Hetzner, Digital Ocean, Hostinger, a Raspberry Pi, whatever): ```bash # install Hermes curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash # set up the Telegram gateway hermes gateway setup # paste your bot token from @BotFather # paste your numeric Telegram user ID (use @userinfobot) — NOT your @username # start the daemon hermes daemon start ``` Message your bot. It responds. Now add a job: ``` > every morning at 8am, summarize my GitHub notifications and send them to me here ``` Hermes writes a cron entry, stores your preference in memory, and pings you at 8am tomorrow. Leave the VPS running. **Common gotcha:** the Telegram allowlist needs your numeric user ID (a number like `123456789`), not your `@handle`. Using the handle silently accepts messages from anyone who guesses your handle. Use `@userinfobot` on Telegram to get your numeric ID. **Why this is a good first workflow:** you walk away with a running always-on agent for $5/month. Every other workflow you build from here reuses this setup. ### Example 3 — Daily cron briefing No bot, no chat. Just a scheduled job that emails or DMs you one summary every morning. ```bash hermes > every weekday at 7:30am, collect: (1) top 10 HN posts overnight, (2) my unread GitHub notifications, (3) weather in Seattle. Send as a plain-text email to me@example.com. ``` Hermes schedules the cron job, remembers your email and city, and starts running it. Wake up tomorrow and check your inbox. **Why this is a good first workflow:** it's low-surface, always-on, and teaches you how Hermes treats scheduled workflows as first-class citizens. --- ## 7. The learning loop This is the section worth slowing down for. If you understand the learning loop, you understand why Hermes is shaped the way it is. ### Why Hermes gets better over time After every task — or every five-ish tool calls — Hermes runs a short retrospective against itself: *did that work? what took too long? what did the user reject? is there a reusable pattern here?* When the answer is yes, it writes a new skill or updates memory. The next time you make a similar request, Hermes reaches for the skill first and skips the rediscovery. This is the opposite of a stateless chat. A stateless chat throws away everything at the end of each conversation. Hermes writes it down. ### Bounded memory: a feature, not a bug Memory is stored in three places: - `MEMORY.md` — short-term, ~2,200 characters max. What the agent is working on right now. - `USER.md` — facts about you, ~1,375 characters max. Name, preferences, role, constraints. - **Session search** (FTS5 full-text index) — every past conversation is searchable. The small caps are deliberate. Unlimited memory sounds attractive until you realize that's how agents turn into junk drawers of stale context. Hermes forces consolidation: when `MEMORY.md` fills up, the agent has to decide what's worth keeping. That discipline keeps the working context tight and the model focused. If you want unlimited semantic memory, there are eight community memory providers (Honcho, Mem0, Hindsight, Supermemory, and others) that plug in on top. See [best memory providers →](/lists/best-memory-providers). ### Skills: executable procedures, not notes Skills are the part everyone undersells. A skill is a markdown file at `~/.hermes/skills//SKILL.md` that describes: - **When** to trigger it (a short description the orchestrator reads) - **How** to run it (instructions, tool calls, example input/output) - **Context** it needs (which files, which APIs) Claude Code's memory stores *facts* about you ("prefers bullet points"). Hermes stores *procedures* ("the research-filter-format workflow that produces bullet points the way you want them"). That's a meaningful difference. Facts inform the model; procedures get reused directly. ### The 5-tool-call rule Skills don't auto-generate after every task — that'd be noisy. They generate when Hermes detects repetition: usually after five-plus tool calls on a pattern, or after a user correction that teaches something general. That's why on day one your skills directory is empty, and by day thirty you have 20+ skills running your life. ### What "Harness Engineering" actually means Nous uses the phrase *Harness Engineering* a lot. It's the framing behind the whole product: the LLM is a replaceable component, and the real engineering work happens in the layers around it. There are five: instruction layer (how you talk to the model), constraint layer (what it's allowed to do), feedback layer (how errors flow back), memory layer (what persists), and orchestration layer (how multiple tools and calls are stitched together). Hermes is an opinionated implementation of those five layers. Swap the model, keep the harness. --- ## 8. Essential skills to install first There are 643 community-contributed skills in the Hub (as of 2026-04-19). Don't try to install them all. Here are five that every Hermes user should have on day one. ### The 643-skill Hub Run `hermes skills browse` to see the catalog. Skills come from four trust tiers: - **Builtin** — ships with Hermes, can't be tampered with. - **Official** — published by Nous, security-audited. - **Trusted** — published by verified community members (OpenAI, Anthropic, VoltAgent, gstack, etc.). - **Community** — everything else; scanned for security issues but read the source before installing. ### Five to install today 1. **LLM Wiki** (builtin) — Karpathy-style condensed reference for any topic. Feed it "transformers" and get a 2-minute primer. Great for ramping on anything Hermes encounters. 2. **gstack** (trusted) — browser automation, QA testing, and design review in one skill. Essential for anyone using Hermes to dogfood websites. 3. **OpenAI taps** (trusted) — expose OpenAI's function-calling primitives as Hermes tools. Useful even if you're not on an OpenAI model. 4. **Manim** (official) — generate mathematical animations from text. Surprisingly addictive for anyone who writes technical content. 5. **security-audit** (official) — scan a repo for common vulnerabilities. Use it before you ship anything public. Install with: `hermes skills install ` ### How to browse the hub ```bash hermes skills browse # interactive browser hermes skills search telegram # keyword search hermes skills info # inspect before installing ``` Every skill shows trust tier, author, description, and recent changes. Read those before running anything in the Community tier. More picks in our curated list: **[Top Skills for Hermes Agent →](/lists/top-skills)** --- ## 9. Where to go next You've installed Hermes, picked a model, shipped one workflow, and understand the learning loop. Here are three paths from here. ### Path 1 — Deeper into agents Build a multi-agent team. One orchestrator, one researcher, one writer, one debugger, each with their own memory and skills. Hermes's delegation system makes this surprisingly clean. Start with our curated list: **[Multi-Agent Frameworks →](/lists/multi-agent-frameworks)**. ### Path 2 — Deeper into tooling Build your own tools and skills. Learn the MCP protocol so your Hermes instance can talk to Notion, Linear, Figma, your internal APIs. This is where the Harness Engineering mental model really pays off. Start with **[Developer Tools →](/lists/developer-tools)**. ### Path 3 — Deeper into infra Run Hermes in production for a team. Docker, systemd, managed cloud templates, Kubernetes. The community has packaged most of it. Start with **[Deployment Options →](/lists/deployment-options)**. ### Bookmark the Atlas The handbook teaches you the fundamentals. The Atlas is where you find the specific tool you need for a specific job, ranked, filtered, and security-reviewed. **[Browse all 280+ projects →](/)**. And if you want the broader picture of where Hermes is right now — stars, PRs, key launches, what's next — read the quarterly report: **[The State of Hermes Agent — April 2026 →](/reports/state-of-hermes-april-2026)**. --- ## 10. FAQ ### Is Hermes Agent free? Hermes itself is free and open-source (MIT licensed). You pay only for the model API you use. With some API model providers or a local Ollama model, your total cost can be $0. With Claude or GPT, you can easily spend $100+ per month depending on volume. ### Does it work on Windows? Yes — two paths. **WSL2** is the road-tested option: run `wsl --install` in PowerShell, install Ubuntu, then run the standard Linux curl installer from inside WSL. **Native Windows** works via an early-beta PowerShell installer (`irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex`) — Nous's own framing is "not road-tested as broadly," so prefer WSL2 if you're using Hermes for real work. ### Can I run it fully offline? Yes. Install Hermes, pair it with Ollama or LM Studio, and disconnect your network. Memory, skills, and cron all work offline. The catch: local models are weaker at tool calling, so complex multi-step workflows degrade. For offline *coding*, you're fine to an extent based on the capabilities of your local model. For offline *automation with many tool calls*, expect rough edges. ### Do I need a GPU? No — if you use an API provider, any laptop handles Hermes. You need a GPU only if you're running the model locally. ### Is my data sent anywhere? Only to the provider you configure. Hermes has no telemetry, no analytics beacon, no phone-home. Memory, skills, and session logs live on your disk. If you pick a local model, your data never leaves your machine. ### Hermes vs Claude Code — do I have to pick one? No. Most power users run both. Claude Code for coding inside a repo, Hermes for everything outside a repo (automation, monitoring, chat, cron, multi-repo research). They complement rather than compete. Full comparison: **[Hermes vs Claude Code →](/guide/vs-claude-code/)**. ### Will Hermes mess with my existing code? No — not unless you point it at your codebase and ask it to. Hermes is additive: memory, skills, and logs live in `~/.hermes/`. It doesn't touch files outside directories you tell it to work in. If you want stricter sandboxing, enable the Docker backend and approval policies. ### What happens if it breaks something? Hermes has approval policies that force confirmation on destructive operations (deletes, force-pushes, `rm -rf`). Turn them on — they're off by default so new users don't get prompt-bombed. If something goes wrong, every session is logged to `~/.hermes/sessions/` and reversible for most operations. ### Can a team share one Hermes agent? Yes, via profiles. Each profile is an isolated agent instance with its own memory, sessions, skills, and cron state. Create a shared profile on a shared VPS, grant your team access via the messaging gateway allowlist, and you have a team agent. ### Can I use it with Ollama or LM Studio? Yes. Run `hermes model`, pick "custom OpenAI-compatible endpoint," and point at your local server (usually `http://localhost:11434/v1` for Ollama). Everything works identically to the API providers, except tool-calling quality depends on the local model you pick — see [chapter 5](#5-pick-your-model). ### How do I update? ```bash hermes update ``` Hermes self-updates. It tells you what changed, backs up your config, and applies the new version. Current release is v0.21.5 (as of 2026-09-24); the team ships roughly every two weeks. --- ## Where this handbook goes next This is v1. We'll update it regularly. If something is wrong, unclear, or out of date, open an issue on [the Atlas repo](https://github.com/ksimback/hermes-ecosystem) or DM [@ksimback](https://x.com/ksimback). The handbook is the canonical beginner's reference and we want it to stay that way. --- **Written by [Kevin Simback](https://x.com/ksimback)** · maintainer, Hermes Atlas **Last updated:** 2026-10-26 · Version and star figures re-stamp automatically with every site build. **Cited stats:** - 257,151 GitHub stars (as of 2026-10-26) — source: `api.github.com/repos/NousResearch/hermes-agent` - 280+ projects in the Hermes Atlas (as of 2026-10-26) - 643 skills in the community Hub (as of 2026-04-19) **Corrections and feedback:** [open an issue](https://github.com/ksimback/hermes-ecosystem/issues/new) or message on X. --- # Hermes vs Claude Code (/guide/vs-claude-code/) Canonical URL: https://hermesatlas.com/guide/vs-claude-code/ # Hermes Agent vs Claude Code: Which AI Agent Should You Use? By [Kevin Simback](https://x.com/ksimback) · Hermes Atlas maintainer · Updated 2026-04-20 > A satellite page of **[The Hermes Handbook](/guide/)**. Cross-checked against both tools' docs and real community usage as of October 2026. --- ## TL;DR **Claude Code is the best in-repo coding agent you can run today (Codex is good too). Hermes Agent is the best cross-session, multi-channel autonomous agent you can run today. They don't compete — they stack. If you code for a living, you probably want both.** Pick Claude Code if your job is "edit this codebase and commit." Pick Hermes if your job is "run my digital life in the background." Most serious users run them side by side. --- ## The one-minute version Claude Code lives inside a repo. It opens in your terminal, reads your code, writes code, runs tests, commits. It's Anthropic's opinionated coding agent, and it's excellent at what it's designed for. Hermes Agent lives on a server. It remembers what it learns across sessions, writes its own reusable skills, and reaches you through whatever channel you prefer — CLI, Telegram, Discord, email, cron. It's Nous Research's bet that the interesting problems in 2026 are everything *outside* the editor. The frame people reach for is: **Claude Code is a specialist; Hermes is a generalist.** That's roughly right. Specialists are sharper inside their domain; generalists span more domains. You don't pick between them any more than you pick between your IDE and your terminal. --- ## Side-by-side comparison | | **Claude Code** | **Hermes Agent** | |---|---|---| | **Built by** | Anthropic | Nous Research | | **Primary surface** | CLI in a repo + IDE plugins | CLI + Telegram/Discord/email + cron daemon | | **Where it runs** | Your laptop, inside a project | Your laptop *or* a VPS, long-running daemon | | **Model support** | Claude only (Anthropic models) | 18+ providers — Claude, GPT, MiniMax, GLM, DeepSeek, Ollama, custom endpoints | | **Persistent memory** | `CLAUDE.md` files (static, user-maintained) | `MEMORY.md` + `USER.md` + session FTS5 index (active, agent-updated) | | **Learning over time** | None — you edit `CLAUDE.md` manually | Auto-generates skills from repeated patterns (the learning loop) | | **Skills ecosystem** | Slash commands, hooks, MCP servers (rich) | 643-skill Hub + MCP (as of 2026-04-19, from the research bank) | | **Scheduled jobs** | No native cron (wrap externally) | Built-in cron, first-class citizen | | **Messaging channels** | Terminal only | Terminal, Telegram, Discord, email, webhooks | | **Multi-agent / delegation** | Subagents via the Task tool | Native delegation, multi-agent teams, profiles | | **Sandboxing** | Approval prompts, permission system | Approval policies, Docker backend, profile isolation | | **License & openness** | Proprietary (Anthropic) | Open-source (MIT), 257,151 stars as of 2026-10-26 | The two rows that matter most for the decision: **model support** (Anthropic-only vs multi-provider) and **where it runs** (inside a repo vs on a server). --- ## When to pick Claude Code Claude Code is the right tool when your task lives inside source code. - **You're editing a codebase.** Read files, run greps, modify imports, write tests, commit, push, open a PR. Claude Code's workflow is built around exactly this loop, and every feature — hooks, subagents, MCP — reinforces it. - **You want IDE integration.** The VS Code and JetBrains plugins give you inline context while you work. If you pair-program with an agent, Claude Code is the cleanest experience. - **You trust Anthropic's models.** Claude Sonnet and Opus are best-in-class for code reasoning. If your preference is "always use the smartest available model," Claude Code locks you into that by design. - **You want a polished, opinionated experience.** Anthropic ships a tight product. Less configuration surface, fewer footguns, faster onboarding. Claude Code falls short when the task leaves the repo: running scheduled jobs while you sleep, handling Telegram messages from your phone, keeping context across weeks of unrelated projects, or swapping to a cheaper model when Claude tokens get expensive. --- ## When to pick Hermes Hermes is the right tool when your task crosses sessions, channels, or models. - **You want an always-on agent.** Hermes runs as a daemon. It wakes on cron, responds to messages, handles webhooks, and keeps going while your laptop is closed. - **You want cross-channel access.** Message Hermes from Telegram during a commute. Check back on the CLI that evening. Same agent, same memory, same skills. Claude Code doesn't leave the terminal. - **You want the agent to get better over time.** The learning loop — five-tool-call retrospectives, auto-generated skills — compounds quietly. Day thirty doesn't feel like day one. - **You want model flexibility.** Swap from Claude to GPT to GLM-5 to local Ollama with one command. No code changes, no vendor lock-in. Cheap models for cheap jobs, frontier models for real work. - **You want it to be yours.** MIT-licensed, 257,151 stars (as of 2026-10-26), self-hostable on a $5 VPS. The code is open, the data lives on your disk, and nothing phones home. Hermes falls short when you need deep in-editor coding support. It can read and write code, but it's not optimized for the minute-by-minute code-edit-test loop the way Claude Code is. Use Claude Code for that, and use Hermes around it. --- ## The stacking play: most power users run both The single biggest myth in agent discourse is that these tools compete. They don't. Walk through a typical day for someone who runs both: - **Morning** — Hermes DMs you a Telegram briefing: overnight HN posts, unread GitHub notifications, a market alert you set up last week. - **Mid-morning** — you sit down to code. Open Claude Code in your repo. Pair-program through a tricky migration. Claude writes tests, you review, it commits. - **Afternoon** — a long-running task kicks off. Hermes handles it on the VPS. You get back to coding with Claude Code. Context-switching cost: zero. - **Evening** — Hermes pings you on Telegram: the task finished, here's the summary. You skim it from your phone. Neither tool could do this alone. Claude Code can't wake you up in the morning with a briefing. Hermes can't do the thirty-minute code-review dance as smoothly as Claude Code. Together they cover your whole day. The cost calculus is also friendlier than it looks. Claude Code runs on Anthropic tokens — pay-per-use. Hermes runs on whichever model you pick, and for background/automation tasks you can use cheap models (DeepSeek, GLM, local Ollama) and save Claude tokens for the in-editor coding where quality really matters. --- ## Migrating from OpenClaw If you're coming from OpenClaw and trying to decide where to land, here's the short version: - **OpenClaw → Claude Code** is the natural migration for the *coding* subset of what OpenClaw did. If OpenClaw was mostly your "run shell workflows in a repo" tool, Claude Code is the upgrade path. - **OpenClaw → Hermes** is the natural migration for the *automation* subset. If OpenClaw was mostly your "run scripts on a schedule and notify me" tool, Hermes is the upgrade path. - **Both** is fine too. OpenClaw users who run the full gamut tend to split the workload: Claude Code takes the repo, Hermes takes the cron jobs. Nous ships a migration tool that ports OpenClaw configs to Hermes skill format — friction is minimal. --- ## FAQ ### Can Hermes use Claude models? Yes. Hermes supports 18+ providers including Anthropic. You can run Hermes with Claude Sonnet as the model if you want the same underlying brain as Claude Code. The difference is the harness around the model, not the model itself. ### Does running both mean paying twice? No. They share a model bill if you point them at the same provider, and nothing about Claude Code prevents Hermes from existing or vice versa. The operational overhead is also low — Claude Code on your laptop, Hermes on a $5 VPS, you never think about the split. ### Can Hermes replace Claude Code for coding? For *simple* coding tasks — "refactor this file," "add a test" — yes. For sustained in-repo work with review cycles, Claude Code's editor integration and opinionated UX are genuinely better. The community consensus: use Hermes for one-shot code tasks and coding on the move (via Telegram), use Claude Code for sit-down coding sessions. ### Is Hermes production-ready? As of 2026-10-26, yes, with caveats. 257,151 GitHub stars, an active Nous team shipping every two weeks, and a ~650-project community ecosystem. Real companies run Hermes in production. The honest caveats: the skill ecosystem is younger than Claude Code's, and some integrations still have rough edges. Read the **[State of Hermes report →](/reports/state-of-hermes-april-2026)** for the full picture. --- ## What next - **New to Hermes?** Start with the full beginner's walkthrough: **[The Hermes Handbook →](/guide/)** - **Want the tool landscape?** Browse **[all 280+ projects in the Atlas →](/)** - **Curious about the ecosystem?** Read the **[State of Hermes — April 2026 report →](/reports/state-of-hermes-april-2026)** --- **Written by [Kevin Simback](https://x.com/ksimback)** · maintainer, Hermes Atlas **Last updated:** 2026-10-26 · Version and star figures re-stamp automatically with every site build. **Cited stats:** - 257,151 GitHub stars (as of 2026-10-26) — source: `api.github.com/repos/NousResearch/hermes-agent` - 643 skills in the community Hub (research bank snapshot, as of 2026-04-19) **Corrections and feedback:** [open an issue](https://github.com/ksimback/hermes-ecosystem/issues/new) or message on X. --- # Install Hermes Agent (/guide/install/) Canonical URL: https://hermesatlas.com/guide/install/ Skip to content hermes atlas 280·repos hermes·v0.21.5 ★ star this repo home ecosystem lists skills use cases handbook masterclass dev reports source home / handbook / install handbook · satellite · install How to install Hermes Agent The complete 2026 setup guide for every platform — with dedicated pages for Windows , macOS , Linux , Raspberry Pi , and VPS , plus the full troubleshooting tree for every common install error. By Kevin Simback · Hermes Atlas maintainer · Updated 2026-10-26 · ~8 min read TL;DR — Hermes Agent installs with a single curl command on macOS, Linux, or Windows via WSL2. The installer takes two to three minutes end-to-end and is maintained in lockstep with the main repo. This guide covers Hermes Agent v0.21.5 ( current release as of October 2026; 257,151 GitHub stars as of 2026-10-26). TL;DR One curl command. Two to three minutes. Works on macOS, Linux, and Windows via WSL2. curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash source ~/.bashrc # or: source ~/.zshrc hermes # start chatting If that worked, skip to first run and model provider . If it didn't, the troubleshooting tree covers the nine failure modes I've seen, in the order you should check them. Want the full walkthrough for your exact setup? Each platform has a dedicated page with its own installer specifics, pitfalls, and FAQ: Windows 10/11 · macOS (Apple Silicon) · Linux & servers · Raspberry Pi · VPS . Before you start Supported OSes (as of v0.21.5): macOS — Apple Silicon (M1/M2/M3/M4) only , Tier 1. Intel (x86) Macs are explicitly unsupported , as are brew and pip installs. Details: macOS install guide . Windows 10/11 — native is Tier 1 (x86_64 and aarch64), via the PowerShell installer or the Hermes Desktop installer; WSL2 is equally Tier 1 for POSIX workflows. Details: Windows install guide . Linux & WSL2 — Tier 1 (x86_64 and aarch64). Nous tests on the latest Ubuntu; any glibc + systemd + FHS distro is expected to work. Details: Linux install guide . Docker — Tier 1 (x86_64 and aarch64); the always-on path for VPS boxes and Raspberry Pis . Updates by pulling a new image, not hermes update . Termux (Android) and Nix — Tier 2, best-effort. The same curl one-liner works inside Termux (voice excluded); Nix is no longer an explicitly supported path. Prerequisites — Hermes's installer is aggressive about setting up its own stack, so you need almost nothing pre-installed: Git — only hard requirement. A terminal — bash, zsh, and fish all work. ~200 MB of disk for the install itself; budget another 100–500 MB for memory, skills, and session logs as you use it. Model access (optional on first install, required before useful work) — an API key from Anthropic / OpenAI / z.AI / MiniMax / DeepSeek, or a Nous Portal subscription, or a local model via Ollama / LM Studio. The installer handles the rest automatically: uv , Python 3.11, Node.js, ripgrep , ffmpeg , the venv, the global hermes command, and the ~/.hermes/ directory tree. On native Windows it additionally bundles a portable Git Bash (~45 MB MinGit) inside %LOCALAPPDATA%\hermes\git . Install on macOS Apple Silicon only (Tier 1) — Intel Macs, brew , and pip installs are officially unsupported. Two paths: the Hermes Desktop installer (recommended — app + CLI in one), or terminal-only: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.zshrc # macOS default since Catalina hermes version Full macOS guide → — Desktop vs CLI install, the Intel-Mac situation, Mac-specific pitfalls, and the Mac mini always-on setup. Install on Linux Tier 1 on x86_64 and aarch64; the command is identical across distros (make sure git , curl , and xz-utils are present first): curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.bashrc Full Linux guide → — distro notes (Ubuntu, Debian, Fedora, Arch — and why the AUR is a trap), per-user vs FHS layouts, and the complete Ubuntu Server / headless / systemd service-user recipe. Install on Windows Native Windows 10/11 is Tier 1 — no WSL required, no admin rights. Open PowerShell and run: iex (irm https://hermes-agent.nousresearch.com/install.ps1) Or use the Hermes Desktop installer for a double-click install. WSL2 is equally supported and the right pick for POSIX-heavy workflows (it's the standard Linux install inside Ubuntu). Full Windows guide → — the official native-vs-WSL2 guidance, what the installer does, the feature matrix, gateway auto-start at login, and every Windows-specific pitfall. Install on a Raspberry Pi A Pi 4 or 5 with 4+ GB RAM and a 64-bit OS is a legitimate Tier-1 host (aarch64 Linux and aarch64 Docker are both Tier 1). Direct install uses the Linux one-liner above; Docker gives set-and-forget supervision. Full Raspberry Pi guide → — hardware requirements by board, both install paths, and the always-on gateway setup. Install on a VPS A $5 VPS (1 CPU, 1 GB RAM) runs Hermes as an always-on bot or remote backend when paired with a hosted model API. Docker is the recommended path — and do the install over SSH, not your provider's browser console. Full VPS guide → — sizing from the official docs, Docker and direct-install paths, the mandatory-auth security guidance, and connecting Hermes Desktop or your phone to the box. Verify the install Run these three commands. All three should return clean output: hermes version # prints v0.21.5 (or newer) hermes doctor # system health check — every line should be green hermes status # current config + running daemons For a live smoke test that exercises the model layer (skip this until you've configured a provider — see below): hermes chat -q "Hello! What tools do you have available?" You should see a short response plus a list of enabled tools. If this hangs, the model provider isn't reachable — jump to first run and model provider . First run and model provider Run hermes with no arguments on a fresh install to trigger the interactive setup: hermes Hermes walks you through provider selection. Pick one of these four paths: Path 1 — Nous Portal (easiest) Nous Portal is a single subscription that routes across Claude, GPT, GLM, MiniMax, Nous's own models, and many more via one auth. Sign in with OAuth from the CLI when prompted. One flat monthly bill, no key management. Most people end up here eventually. Path 2 — Bring your own API key Paste a key from Anthropic ( sk-ant-... ), OpenAI ( sk-... ), z.AI, MiniMax, or DeepSeek when prompted. You can swap later with hermes model . Path 3 — Local model via Ollama Install Ollama first ( ollama.com ), pull a tool-calling-capable model (Gemma 4 26B is the current community pick; Qwen 3.5 also works well), raise Ollama's context window (Hermes needs 64K; Ollama defaults to 4K), then point Hermes at it. Local models are great for coding and chat but weaker at multi-step tool chains — the full tradeoff is in chapter 5 of the handbook . Path 4 — Skip for now You can install Hermes without configuring a model and wire one up later with hermes model . Useful if you're installing on a VPS and want to set up the Telegram gateway first. Troubleshooting common install errors Check these in order. The top three catch about 90% of failures. 1. "Command not found: hermes" Your shell didn't pick up the new PATH. Open a fresh terminal window, or run source ~/.bashrc (or ~/.zshrc , or ~/.config/fish/config.fish for fish). If that still doesn't work, check that ~/.hermes/bin is in your PATH: echo $PATH | tr ':' '\n' | grep hermes . 2. "Provider error: invalid API key" Trailing whitespace is the #1 cause. Paste with care, or use the heredoc approach: hermes config set model.api_key "$(cat)" then paste and hit Ctrl-D. Second most common cause: wrong provider selected for the key type. 3. Windows: "bad interpreter", "cannot execute", or curl errors You ran the Linux curl ... | bash command from PowerShell or cmd. That path is for WSL only. Either open your Ubuntu (WSL) terminal and rerun the bash installer, or use the native PowerShell installer instead: irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex . 4. "Permission denied" during install Usually caused by running the curl command under sudo . Don't. Hermes installs per-user under ~/.hermes/ and doesn't need root. If you already ran it as root, sudo rm -rf ~/.hermes/ /root/.hermes/ and retry as your normal user. 5. "uv: command not found" mid-install The installer failed between installing uv and using it — usually because a previous interrupted run left a half-configured state. Simply re-run the install command; it's idempotent. 6. Python version mismatch You have Python 3.9 or older in PATH and something is resolving to that first. The installer pins Python 3.11 in its own venv, but if you see a version error, drop to the manual install below, which gives you explicit control. 7. npm errors ("ENOENT", "EACCES") Node.js didn't install cleanly. Delete ~/.hermes/ , reinstall Node via your OS package manager ( brew install node on Mac, apt install nodejs npm on Ubuntu), then rerun the Hermes curl installer. 8. ffmpeg / ripgrep missing (macOS Apple Silicon) Homebrew path mismatch — Apple Silicon's Homebrew lives at /opt/homebrew/bin , not /usr/local/bin . Add eval "$(/opt/homebrew/bin/brew shellenv)" to your ~/.zshrc and rerun. 9. Installer hangs downloading the hermes binary GitHub release download from a rate-limited or corporate-firewalled network. Set export GITHUB_TOKEN=... (any personal access token) before rerunning, or use the manual install . Manual installation When the curl installer fails and you want step-by-step control: git clone --recurse-submodules https://github.com/NousResearch/hermes-agent.git cd hermes-agent # install uv (Python package manager) curl -LsSf https://astral.sh/uv/install.sh | sh # create venv + install Python deps uv venv venv --python 3.11 export VIRTUAL_ENV="$(pwd)/venv" uv pip install -e ".[all]" # install Node dependencies npm install # create the hermes directory tree mkdir -p ~/.hermes/{cron,sessions,logs,memories,skills,pairing,hooks,image_cache,audio_cache,whatsapp/session} cp cli-config.yaml.example ~/.hermes/config.yaml touch ~/.hermes/.env # symlink hermes to ~/.local/bin for PATH convenience ln -s "$(pwd)/bin/hermes" ~/.local/bin/hermes Add ~/.local/bin to your PATH if it isn't already. Verify with hermes version . Uninstall or clean reinstall Complete uninstall — removes everything including memory, skills, and config: rm -rf ~/.hermes/ Reset config but keep memory and skills : hermes config reset Clean reinstall — useful when something is wedged: rm -rf ~/.hermes/ curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash Get the ecosystem inside your agent Install the hermes-atlas MCP server so Claude Desktop, Cursor, Claude Code, or any MCP-aware client can search the catalog, fetch project summaries, and answer free-form questions about the Hermes ecosystem mid-chat. Five tools: search_projects , get_project , list_by_category , get_guide , ask_atlas . Recommended — one command Run this in a terminal. The installer detects your OS, finds the right config file for your client, and safely merges in the hermes-atlas entry without touching anything else: npx -y hermes-atlas-mcp install --client claude-desktop Replace claude-desktop with cursor or claude-code as needed. Add --print first if you want to preview the exact diff without writing anything. Then fully quit and reopen the client — closing the window isn't enough, the whole process has to restart. In a new chat, click the tool icon (usually at the bottom of the message box) and you'll see the five tools listed. To remove later: npx -y hermes-atlas-mcp uninstall --client claude-desktop Manual install — Claude Desktop If you'd rather edit the config yourself, or the installer doesn't work on your setup, here's the full walkthrough. Step 1 — open the config file The easiest way is through Claude Desktop's built-in button: Open Claude Desktop. Click the Settings gear (or Cmd/Ctrl+, ). Select the Developer tab on the left. Click the Edit Config button. The file opens in your default text editor. If you'd rather find it by path: macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json (usually C:\Users\YOU\AppData\Roaming\Claude\claude_desktop_config.json ) Linux: ~/.config/Claude/claude_desktop_config.json Step 2 — add the hermes-atlas entry If the file is empty, or doesn't exist, paste this as the full contents: { "mcpServers": { "hermes-atlas": { "command": "npx", "args": ["-y", "hermes-atlas-mcp"] } } } If the file already has content, merge the new entry into the existing mcpServers block. For example, if your file currently looks like this: { "mcpServers": { "filesystem": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path"] } } } ...change it to this (add a comma after the filesystem block, then the new hermes-atlas object): { "mcpServers": { "filesystem": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path"] }, "hermes-atlas": { "command": "npx", "args": ["-y", "hermes-atlas-mcp"] } } } If the file has top-level settings like preferences or anything other than mcpServers , leave those alone — only merge into the mcpServers object (or add it if it doesn't exist yet). Step 3 — save and fully restart Claude Desktop Save the file. Then fully quit Claude Desktop — closing the window isn't enough, the background process has to restart. macOS: Cmd+Q with Claude Desktop focused, or right-click the dock icon → Quit. Windows: File → Exit, or right-click the taskbar icon → Close window, or kill it in Task Manager if a Claude process lingers. Reopen Claude Desktop normally. Step 4 — verify Start a new chat. Click the tool / attachment icon at the bottom of the message box. You should see five tools listed under hermes-atlas : search_projects get_project list_by_category get_guide ask_atlas If they're missing, most-likely causes in order: You didn't fully quit Claude Desktop. Quit and reopen again. The JSON isn't valid (a missing comma, extra trailing comma, unbalanced brace). Paste the file into any online JSON validator. You don't have Node.js installed (the npx command needs it). Install from nodejs.org — any LTS version works. Manual install — Cursor File: ~/.cursor/mcp.json (global, applies to every project) or .cursor/mcp.json at your project root (per-project). Use the same JSON shape as Claude Desktop above. Restart Cursor. Manual install — Claude Code Easiest: inside a Claude Code session, run /mcp — the built-in UI walks you through adding a server without touching any file. Otherwise, edit ~/.claude.json using the same shape. Continue, Windsurf, Zed, other MCP clients Any MCP-compatible client works the same way. Configure a server named hermes-atlas that runs npx -y hermes-atlas-mcp via stdio. The client docs will point you at the right config file. Source: github.com/ksimback/hermes-atlas-mcp · npm . MIT-licensed, experimental (0.x), batch releases weekly. What to do next You're installed. The next three handbook chapters walk you through the mistakes most people make on day one: Pick your model — where most first setups silently fail. Don't use small (8B-and-under) local models for agent work. Your first workflow — three concrete examples (coding assistant, Telegram bot, cron automation). Pick one and ship it today. Essential skills to install first — five community skills that should be on every Hermes install on day one. FAQ Does Hermes Agent work on bare Windows? Yes — native Windows 10/11 is a Tier 1 platform. Run iex (irm https://hermes-agent.nousresearch.com/install.ps1) in PowerShell (no admin rights), or use the Desktop installer. It installs to %LOCALAPPDATA%\hermes and bundles a portable Git Bash. Everything except the dashboard's embedded terminal runs natively; WSL2 is equally supported for POSIX workflows. Full details: the Windows install guide . Does Hermes work on Apple Silicon (M1, M2, M3, M4)? Yes, natively — Apple Silicon is Tier 1. The installer detects arm64 and pulls native binaries; no Rosetta required. Intel (x86) Macs are explicitly unsupported — see the macOS install guide . Can I run Hermes Agent on a Raspberry Pi or low-end VPS? Yes. Hermes itself runs comfortably on a $5 VPS (1 CPU, 1 GB RAM) or a Raspberry Pi 4/5 with 4+ GB RAM — we maintain dedicated Raspberry Pi and VPS setup guides. The practical constraint is not Hermes but the model — pair it with a hosted API (Nous Portal, Anthropic) and the agent host stays lightweight. How much disk space does Hermes Agent use? About 200 MB for a fresh install. Memory, skills, and session logs accumulate in ~/.hermes/ over time — budget another 100–500 MB depending on how heavily you use it. Can I run Hermes Agent fully offline? Yes. Install Hermes, pair it with Ollama or LM Studio, disconnect the network. Memory, skills, cron, and file tools all work offline. Local models are weaker at multi-step tool chains, so complex workflows may degrade — but single-shot chat and coding work fine. Do I need Docker to install Hermes? No. The official installer is a native binary install; Docker is not required. Community-maintained Docker images exist (browse the deployment options list on Hermes Atlas) if you prefer containerized deploys, but the path of least resistance is the curl installer. What if the curl install fails mid-way? Re-running the same curl command is safe — the installer is idempotent. If it fails a second time, fall back to the manual install above. Written by Kevin Simback · maintainer, Hermes Atlas Last updated: 2026-10-26 · Version and star figures re-stamp automatically with every site build. Cited stats: 257,151 GitHub stars (as of 2026-10-26) — source: api.github.com/repos/NousResearch/hermes-agent Hermes Agent v0.21.5 — release notes Corrections and feedback: open an issue or message @ksimback on X. if this was useful, drop a ★ on the atlas repo → back to The Hermes Handbook → newsletter · free · 1–2× / month subscribe handled by beehiiv · privacy hermes atlas · curated by ksimback · suggest a repo · privacy v2 · 2026.04 --- # Install Hermes Agent on Windows 10/11 (/guide/install/windows/) Canonical URL: https://hermesatlas.com/guide/install/windows/ # How to Install Hermes Agent on Windows 10/11: PowerShell, Desktop Installer, or WSL2 The Windows install guide. Live version: https://hermesatlas.com/guide/install/windows/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR Native Windows is **Tier 1** — Hermes runs on Windows 10 and 11 (x86_64 and aarch64) with no WSL, no Cygwin, no Docker. Three install paths: 1. **PowerShell one-liner** (fastest if you're in a terminal): `iex (irm https://hermes-agent.nousresearch.com/install.ps1)` — no admin rights required. 2. **Hermes Desktop installer** (recommended by Nous for most people): download the `.exe` from the official site; on first launch it runs `install.ps1` under the hood, and the GUI and CLI share the same install. 3. **WSL2** — only if you specifically want a POSIX environment (see below for the official when-to-pick guidance). This guide covers Hermes Agent **v0.21.5**. ## What the PowerShell installer does - Installs everything to `%LOCALAPPDATA%\hermes\` and adds `hermes` to your **User PATH** — open a new terminal after it finishes. No admin rights, no UAC. - Bootstraps `uv`, Python 3.11, Node.js 26 (winget or a portable tarball), and — if `git` isn't already on PATH — a self-contained PortableGit (~45 MB) under `%LOCALAPPDATA%\hermes\git`. - Sets `HERMES_GIT_BASH_PATH` so Hermes can run shell commands through Git Bash (the same strategy Claude Code uses on Windows). - Runs the `hermes setup` wizard at the end (skip with `-SkipSetup`). Installer parameters (scriptblock form required): `-Branch`, `-Commit`, `-Tag` (pin a version), `-NoVenv`, `-SkipSetup`, `-HermesHome`, `-InstallDir`. ## What works natively Per the official feature matrix, everything except one feature runs natively on Windows: CLI, interactive TUI (`hermes --tui`), the full messaging gateway (Telegram, Discord, Slack, WhatsApp, 15+ platforms), cron scheduler, browser tool, MCP servers, local Ollama/LM Studio, web dashboard, and auto-start at login (via Scheduled Tasks, no admin). The one exception: the dashboard's `/chat` embedded terminal pane needs a POSIX PTY and is WSL2-only. ## Native or WSL2? Both are Tier 1. Official guidance: pick **WSL2** if you want the dashboard's embedded terminal, you do POSIX-heavy development and want Hermes on the same Linux filesystem as your tools, or you already maintain WSL2. **Native is fine — or better** — for everyone else: you skip crossing the WSL↔Windows boundary every time you touch a file or URL. WSL2 path: `wsl --install` in Admin PowerShell, reboot, then run the Linux installer inside Ubuntu: `curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash`. Native data lives under `%LOCALAPPDATA%\hermes`, WSL data under `~/.hermes` — the two coexist cleanly. ## Gateway at Windows login `hermes gateway install` registers a Scheduled Task (`ONLOGON`, non-elevated — no UAC) with a Startup-folder fallback, and spawns the gateway detached via `pythonw.exe` so a stray Ctrl+C can't kill it. Manage with `hermes gateway status/start/stop/restart/uninstall`. ## Common pitfalls - **`hermes: command not found` right after install** — open a NEW PowerShell window; existing shells don't see the updated User PATH. - **`[scriptblock]::Create(...)` fails** — your `install.ps1` download picked up a UTF-8 BOM; use the plain `irm | iex` form instead. - **`/edit` does nothing** — Hermes defaults `EDITOR=notepad`; to use VS Code set `$env:EDITOR = "code --wait"` (the `--wait` is critical). - **Non-Latin characters show as `?`** — the UTF-8 stdio shim didn't activate; check `HERMES_DISABLE_WINDOWS_UTF8` is unset, or switch to Windows Terminal. - **Weird Node version errors** — an older system Node is earlier on PATH than Hermes's bundled Node 26. ## Uninstall `hermes uninstall` removes the scheduled task, launchers, and the `hermes-agent\` checkout but keeps your config/sessions/skills in `%LOCALAPPDATA%\hermes`. To remove everything: also `Remove-Item -Recurse -Force "$env:LOCALAPPDATA\hermes"`. ## FAQ **Do I need admin rights to install Hermes on Windows?** No. The PowerShell installer writes only to `%LOCALAPPDATA%\hermes` and your User PATH; gateway auto-start uses a non-elevated Scheduled Task. **Is native Windows still "early beta"?** No — Windows 10/11 native is a Tier 1 platform in the official support matrix, alongside macOS and Linux. Only the dashboard's embedded terminal pane is WSL2-only. **Should I install natively or in WSL2?** Native for most people. WSL2 if you want the dashboard's embedded terminal or a real POSIX dev environment shared with your tools. **Where does Hermes install on Windows?** Code at `%LOCALAPPDATA%\hermes\hermes-agent\`, your data (config, keys, sessions, skills) directly under `%LOCALAPPDATA%\hermes\`. Reinstalls replace only the checkout; your data survives. **Does the messaging gateway (Telegram/Discord) work on native Windows?** Yes — the full gateway is in the native feature matrix, and `hermes gateway install` keeps it running at login via Scheduled Tasks. **Windows on ARM?** Yes — the official matrix lists Windows 10/11 on both x86_64 and aarch64 as Tier 1. --- # Install Hermes Agent on macOS (/guide/install/macos/) Canonical URL: https://hermesatlas.com/guide/install/macos/ # How to Install Hermes Agent on macOS (Apple Silicon) The macOS install guide. Live version: https://hermesatlas.com/guide/install/macos/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR Two supported paths on a Mac, both Tier 1 on **Apple Silicon** (M1–M4): 1. **Hermes Desktop installer** (recommended by Nous): download from the official site and run it — you get the desktop app and the CLI in one shot, sharing the same config and data. 2. **CLI-only curl install**: `curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash`, then `source ~/.zshrc` and run `hermes`. Two paths that are explicitly **unsupported**: `brew install hermes-agent` and `pip`/`uv tool install` — the official platform-support page says they may be broken now, may break more, and compat code can be removed at any point. This guide covers Hermes Agent **v0.21.5**. ## Intel Macs are unsupported The official support matrix lists **macOS on Intel (x86) processors as unsupported** — only Apple Silicon is Tier 1. If you're on an Intel Mac, the practical alternatives are running Hermes on a Linux box/VPS you SSH into, or the Docker image (Tier 1 on x86_64) on other hardware. Don't expect the installer to keep working on Intel. ## Prerequisites Just **Git** (`git --version`). The installer handles the rest: `uv`, Python 3.11 (no sudo), Node.js 26 (existing Node 22.22+/24.11+/26+ is used as-is), ripgrep, and ffmpeg. For the desktop app it also needs a working compiler toolchain to build native modules. ## Install and verify ``` curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.zshrc # macOS default shell since Catalina hermes version # prints v0.21.5 (or newer) hermes doctor # health check — every line should be green ``` Code lands in `~/.hermes/hermes-agent/`, the `hermes` command at `~/.local/bin/hermes`, and your data (config, keys, sessions, skills, memory) in `~/.hermes/`. First run: `hermes` starts the provider wizard. Fastest path is `hermes setup --portal` — one Nous Portal login covers 300+ models plus the Tool Gateway. Already running Hermes elsewhere? `hermes import` restores a full backup. If you installed CLI-only and want the app later: `hermes desktop` installs and launches Hermes Desktop against your existing config. ## FAQ **Does Hermes work on Apple Silicon (M1, M2, M3, M4)?** Yes — macOS on Apple Silicon is Tier 1. The installer pulls native arm64 binaries; no Rosetta. **Does Hermes work on Intel Macs?** No — Intel Macs are explicitly listed as unsupported in the official platform matrix. Use a Linux machine, a VPS, or Docker on other hardware instead. **Can I install Hermes with Homebrew?** No — `brew install hermes-agent` is an unsupported path per the official docs. Use the Desktop installer or the curl one-liner. **Should I use the Desktop installer or the curl install?** Desktop installer if you want the app (Nous recommends it as the easy path); curl if you're terminal-only. They share the same agent core, config, and data — and `hermes desktop` upgrades a CLI install to the app any time. **Is a Mac mini a good always-on Hermes host?** An Apple Silicon Mac mini works well — it's a Tier 1 platform and popular for exactly this. For headless always-on setups, compare the Docker/VPS route in our modes guide. **How much disk space does it need?** Roughly 200 MB for a fresh install; budget another 100–500 MB for sessions, skills, and memory as you use it. --- # Install Hermes Agent on Linux (/guide/install/linux/) Canonical URL: https://hermesatlas.com/guide/install/linux/ # How to Install Hermes Agent on Linux (Ubuntu, Debian, Fedora, Arch) The Linux install guide. Live version: https://hermesatlas.com/guide/install/linux/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR One command on any supported distro: ``` curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.bashrc hermes ``` Linux (x86_64 and aarch64) is **Tier 1**. Nous tests on the latest Ubuntu and WSL2; per the official matrix, "if your distro has glibc, systemd, and follows the Filesystem Hierarchy Standard, it's likely to work pretty well." This guide covers Hermes Agent **v0.21.5**. ## Prerequisites - **Git**, plus **curl** and **xz-utils** (the installer downloads Node.js as a `.tar.xz`): `sudo apt install git curl xz-utils` on Debian/Ubuntu. - For the desktop app only: `build-essential` (g++) to compile native modules. - The installer handles the rest with no sudo: `uv`, Python 3.11, Node.js 26, ripgrep, ffmpeg. ## Install layout: per-user vs system-wide - **Per-user (default):** code at `~/.hermes/hermes-agent/`, launcher symlinked to `~/.local/bin/hermes`, data at `~/.hermes/`. - **Root mode** (`curl … | sudo bash`): FHS layout — code at `/usr/local/lib/hermes-agent/`, binary at `/usr/local/bin/hermes`. Useful for shared machines; per-user config still lives in each user's `~/.hermes/`. ## Ubuntu Server / headless / service-user installs Running Hermes as a dedicated unprivileged user (e.g. a `hermes` systemd service account) is officially supported. The only step that genuinely needs root is Playwright's Chromium system libraries: 1. Once, as an admin: `sudo npx playwright install-deps chromium`. 2. As the service user, run the normal installer — it detects missing sudo and degrades gracefully. Headless and don't need browser automation? Add `--skip-browser` (and `--skip-computer-use`). 3. Make sure `~/.local/bin` is on the service user's PATH. 4. Verify with `hermes doctor`. 5. Running the messaging gateway from this account? `sudo loginctl enable-linger ` so the user-level service survives logout and starts at boot. The same pattern works on Arch, Fedora/RHEL, and openSUSE — those distros don't support Playwright's `--with-deps`, so the installer prints the exact `dnf`/`zypper` commands an admin should run. ## Distro notes - **Ubuntu / Debian** — the tested reference platform. Fresh minimal cloud image: `apt-get install -y git curl xz-utils` first. - **Fedora / RHEL / openSUSE** — supported via the same installer; admin installs Chromium system libraries separately (commands printed by the installer). - **Arch** — the installer works (same sudo-detection logic, via pacman). **The AUR package is explicitly unsupported** — use the official installer. - **Nix / NixOS** — no longer an explicitly supported install path (Tier 2, best-effort): the official matrix says it "breaks often due to node.js packaging woes." There's a dedicated Nix setup guide with a flake and NixOS module if you accept that tradeoff. ## Updating `hermes update` auto-detects the git-installer layout and updates in place. (Docker installs update by pulling a new image instead.) ## FAQ **How do I install Hermes Agent on Ubuntu?** `curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash`, then `source ~/.bashrc`. Ubuntu is the distro Nous tests against. **Does the installer need sudo?** No for the core install — it's per-user under `~/.hermes/`. Root is only needed once for Playwright's Chromium system libraries (or skip browser tools with `--skip-browser`). **Which distros are supported?** Latest Ubuntu and WSL2 are tested; anything with glibc, systemd, and FHS is expected to work. Alpine (musl) doesn't fit that description. **Can I install from the AUR on Arch?** No — AUR installs are explicitly unsupported. Run the official installer on Arch instead. **How do I keep the gateway running on a server?** Install as a service user, run `hermes gateway setup` (it offers a systemd user unit), and enable lingering: `sudo loginctl enable-linger `. **What about NixOS?** Tier 2 / best-effort — there's an extensive official Nix guide, but releases may break it. Docker or an FHS distro is the supported path. --- # Install Hermes Agent on a Raspberry Pi (/guide/install/raspberry-pi/) Canonical URL: https://hermesatlas.com/guide/install/raspberry-pi/ # How to Install Hermes Agent on a Raspberry Pi (4 & 5) The Raspberry Pi install guide. Live version: https://hermesatlas.com/guide/install/raspberry-pi/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR Yes, Hermes Agent runs on a Raspberry Pi — there's no Pi-specific build because none is needed: **Linux on aarch64 is Tier 1**, and so is the official Docker image on aarch64. A Pi 4 or Pi 5 with **4+ GB RAM** running a **64-bit OS** (Raspberry Pi OS 64-bit or Ubuntu Server) is the sweet spot. Two install paths: 1. **Direct install** (simplest): the standard Linux one-liner on Raspberry Pi OS 64-bit — `curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash`. 2. **Docker** (best for always-on): `docker run` the official `nousresearch/hermes-agent` image (published for aarch64), with s6-supervised gateway auto-restart. The practical constraint isn't Hermes — it's the model. Pair the Pi with a hosted API (Nous Portal, Anthropic, OpenAI) and the agent host stays lightweight; don't plan on running local LLM inference on the Pi itself. This guide covers Hermes Agent **v0.21.5**. ## Hardware requirements - **64-bit (aarch64) OS is required** — official support is for aarch64 Linux; use Raspberry Pi OS **64-bit** or Ubuntu Server 64-bit, not a 32-bit (armv7) image. - **Pi 4 / Pi 5 with 4 GB+ RAM recommended.** Docker minimums from the official docs: 1 GB RAM / 1 core, 2–4 GB recommended — browser automation (Playwright/Chromium) is the most memory-hungry feature; skip it (`--skip-browser`) on smaller Pis. - A Pi 3 technically has an aarch64 CPU but only 1 GB RAM — enough for a gateway-only setup without browser tools, but tight. Pi Zero–class boards are not realistic hosts. - Disk: ~200 MB for the install, plus 500 MB–2 GB+ as sessions and skills grow. Use a quality SD card or, better, USB/NVMe boot. ## Path 1 — direct install on Raspberry Pi OS Raspberry Pi OS 64-bit is Debian-based, so the Pi is just a Tier-1 Linux aarch64 box: ``` sudo apt install -y git curl xz-utils curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash source ~/.bashrc hermes version # prints v0.21.5 (or newer) ``` For an always-on Telegram/Discord bot: `hermes gateway setup` (offers a systemd user unit) and `sudo loginctl enable-linger ` so the gateway survives logout and starts at boot. Headless Pi? Add `--skip-browser` to the installer to skip Chromium entirely. ## Path 2 — Docker (recommended for set-and-forget) The official image is published for aarch64 and supervises the gateway with s6 (auto-restart on crash): ``` mkdir -p ~/.hermes docker run -it --rm -v ~/.hermes:/opt/data nousresearch/hermes-agent setup docker run -d --name hermes --restart unless-stopped \ -v ~/.hermes:/opt/data -p 8642:8642 \ nousresearch/hermes-agent gateway run ``` Updating is `docker pull` + recreate (Docker installs intentionally don't support `hermes update`). Never run two gateway containers against the same data directory. ## What people actually run on Pis Community reports in our user-story corpus include a Raspberry Pi 5 running Hermes 24/7 as an always-on personal agent and Pi-hosted gateways on residential IPs. Treat these as community anecdotes rather than official benchmarks — but they match what the Tier-1 aarch64 support implies. ## FAQ **Can Hermes Agent run on a Raspberry Pi 5?** Yes — aarch64 Linux and aarch64 Docker are both Tier 1. A Pi 5 (4 or 8 GB) handles the agent, gateway, and cron comfortably with a hosted model API. **Can it run on a Raspberry Pi 4?** Yes — same paths. Prefer the 4 GB or 8 GB model; on 2 GB, skip browser tools. **What about a Raspberry Pi 3?** Borderline: it's aarch64 but has 1 GB RAM — the documented Docker minimum with no headroom. Gateway-only without browser tools can work; expect swap pressure. **Do I need a 64-bit OS?** Yes. Official support targets aarch64; install Raspberry Pi OS 64-bit or Ubuntu Server 64-bit, not the 32-bit image. **Can the Pi run the model locally?** Not realistically — pair Hermes on the Pi with a hosted API (Nous Portal, Anthropic, OpenAI) or a model server on beefier hardware on your LAN. **Docker or direct install on the Pi?** Docker for set-and-forget uptime (supervised auto-restart, clean upgrades by pulling a new image); direct install for the lightest footprint and `hermes update`. --- # Install Hermes Agent on a VPS (/guide/install/vps/) Canonical URL: https://hermesatlas.com/guide/install/vps/ # How to Install Hermes Agent on a VPS (Always-On Server Setup) The VPS/server install guide. Live version: https://hermesatlas.com/guide/install/vps/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR A **$5 VPS (1 CPU, 1 GB RAM)** is enough to run Hermes as an always-on agent — Telegram/Discord bot, cron jobs, remote backend for Hermes Desktop — as long as the model is a hosted API (Nous Portal, Anthropic, OpenAI), not local inference. Recommended path: **Docker** (`nousresearch/hermes-agent`, Tier 1 on x86_64 and aarch64) with `--restart unless-stopped`; the image's s6 supervisor auto-restarts a crashed gateway. Direct install works too via the standard Linux one-liner. **Connect over SSH, not your provider's browser console** — official docs warn that browser-based VPS consoles (Hetzner Cloud and others) mis-transmit characters like `:` and `@`, silently corrupting `docker run -v/-e` arguments and pasted API keys. This guide covers Hermes Agent **v0.21.5**. ## Sizing From the official Docker resource table: minimum 1 GB RAM / 1 core / 500 MB disk; recommended 2–4 GB RAM / 2 cores / 2 GB+ disk. Browser automation (Playwright/Chromium) is the most memory-hungry feature — a 1 GB box is fine if you skip it. Any glibc/systemd/FHS distro is likely to work; Ubuntu is the tested reference. ## Path A — Docker (recommended) ``` ssh root@ mkdir -p ~/.hermes docker run -it --rm -v ~/.hermes:/opt/data nousresearch/hermes-agent setup docker run -d --name hermes --restart unless-stopped \ -v ~/.hermes:/opt/data -p 8642:8642 \ nousresearch/hermes-agent gateway run ``` All state lives in the mounted `~/.hermes` — the container is stateless, so upgrading is `docker pull` + recreate (no `hermes update` in Docker, by design). One container can host multiple profiles (the officially recommended pattern), each gateway s6-supervised with per-profile rotated logs. Never point two gateway containers at one data directory. ## Path B — direct install (service user) The standard installer, run as a dedicated unprivileged user: `curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash` (add `--skip-browser` on headless boxes to skip Chromium). One-time admin step for browser tools: `sudo npx playwright install-deps chromium`. Then `hermes gateway setup` (installs a systemd user unit) and `sudo loginctl enable-linger ` so the gateway starts at boot and survives logout. ## Security: the part people get wrong Exposing the dashboard or API server on a VPS means a non-loopback bind, and that **engages a mandatory auth gate** — unauthenticated public dashboards were the entry point for a real June 2026 attack campaign (internet scanners drove exposed agents into planting SSH-key backdoors), and the old `--insecure` escape hatch is now a deprecated no-op. Official guidance: - **OAuth via Nous Portal** for anything reachable from the public internet. - **Username/password** only on a trusted LAN or VPN (e.g. Tailscale). - Or bind to `127.0.0.1` and reach the dashboard over an SSH tunnel — no public exposure at all. - The gateway's OpenAI-compatible API server is off by default; enabling it beyond loopback requires `API_SERVER_KEY`. ## Using the VPS from your desktop and phone - **Hermes Desktop** connects to the VPS as a remote gateway: keep `hermes serve` running on the VPS (systemd), then add it under Settings → Gateways in the app — OAuth (Nous Portal) is the preferred provider for a VPS backend. One connection serves every profile on the box. - **Phone**: configure the messaging gateway (`hermes gateway setup`) and talk to your agent over Telegram/Discord/WhatsApp — the reason most people put Hermes on a VPS in the first place. ## FAQ **How small a VPS can run Hermes Agent?** 1 GB RAM / 1 core is the documented minimum (without browser tools); 2–4 GB recommended. The typical $5 tier works with a hosted model API. **Which provider should I use?** Any standard Ubuntu/Debian VPS works — Hermes has no provider-specific requirements. Whatever you pick, do the install over SSH: official docs warn that browser-based VPS consoles (e.g. Hetzner's) corrupt special characters in pasted commands. **Docker or direct install on a VPS?** Docker for supervised auto-restart and clean image-based upgrades; direct install if you want `hermes update` and the lightest footprint. **Is it safe to expose the Hermes dashboard on a VPS?** Only behind the mandatory auth gate — OAuth (Nous Portal) for public reachability; username/password strictly for LAN/VPN; or keep it loopback-only behind an SSH tunnel. `--insecure` no longer bypasses anything. **Can Hermes Desktop connect to my VPS?** Yes — run `hermes serve` on the VPS and add it as a remote gateway in Desktop's Settings → Gateways, protected by OAuth. **How do I update Hermes on the VPS?** Docker: `docker pull nousresearch/hermes-agent:latest`, then recreate the container (data persists in `~/.hermes`). Direct install: `hermes update`. --- # The Hermes Agent Memory Guidebook (/guide/memory/) Canonical URL: https://hermesatlas.com/guide/memory/ # The Hermes Agent Memory Guidebook By [Kevin Simback](https://x.com/KSimback) · Published on X, May 23, 2026 Source: https://x.com/KSimback/status/2058262328496554021 ![The Complete Guide to Hermes Agent Memory](/guide/memory/assets/complete-guide-to-hermes-agent-memory.jpg) TLDR: this is your definitive guide to all things related to memory systems for Hermes Agent. Why create this? Because every week I see new posts or articles describing some new memory tool for Hermes agents and these make me question if my memory setup is the best. So I dug into all of them and broke it down for you. Over the past few months my Hermes agent has been mapping the Hermes ecosystem over at [hermesatlas.com](https://hermesatlas.com). One of the key areas it has covered is memory and it even has a dedicated [memory providers section](/lists/best-memory-providers) for it. ![Best Memory Providers for Hermes Agent](/guide/memory/assets/best-memory-providers-for-hermes-agent.jpg) And let's be honest, there are a LOT of memory related tools available and there are a LOT of write-ups about them. I see new articles on X every week about some new memory setup. It's hard to keep up, and even harder to know if you're doing it all wrong because they all make claims about how certain memory systems are better than others. But many of these write-ups skip the architecture (how memory works in Hermes) or conflate different elements of the memory stack. This article is the culmination of everything I've learned about Hermes agent memory and a guide to help you navigate what makes most sense for your setup. ## Memory is arguably the most important element of an agent setup Without memory, an agent is just a stateless function and no different than a blank ChatGPT window. Every prompt looks like the first prompt. That works for one-shot questions but breaks down the moment you have a use case that needs to know what happened yesterday, remember your preferences, accumulate skills from prior tasks, or coordinate with another agent. A coding session that doesn't remember the conventions you established last Tuesday will reinvent them this Tuesday. A personal assistant agent that doesn't remember your preferences has to ask you the same repeated questions. Without memory, an agent really isn't an agent at all. Memory is what turns an chatbot into something that compounds. Which is why every serious agent harness - OpenClaw, Claude Code, Codex, and our beloved [Hermes Agent](/projects/NousResearch/hermes-agent) - has memory primitives built in, and why a real product category has emerged around dedicated memory infrastructure or agents ([Mem0](/projects/mem0ai/mem0) raised $24M, [Letta](https://www.letta.com/) $10M, plus [Zep](https://www.getzep.com/), Cipher, [Supermemory](/projects/supermemoryai/supermemory), [Hindsight](/projects/vectorize-io/hindsight), etc.). The Hermes Agent take is interesting because Nous Research treats memory as first-class plug-in infrastructure, not a feature. There's a base layer that always runs, a pluggable provider system that lets you choose from 8 architectures (or write your own), and a healthy community plug-in layer on top. That 3-layer stack is what I will explore in depth in this article. ## Hermes Agent memory architecture at a glance Here's what each layer means for you as a Hermes user. Layer 1 - what ships in the box. You get this whether you do anything or not. Two small markdown files the agent uses as its always-visible notebook, plus a local database that archives every session you've ever had. No setup, no config. For many use cases, this is often all you need. Layer 2 - the optional plug-in slot. When you outgrow the native layer (you want semantic recall across sessions, or a system that models your preferences, or token-efficient retrieval at scale) you pick one of 8 official providers. They each take a different architectural bet about what memory should do, and you can run exactly one at a time. Switching providers is a clean start - the new provider doesn't inherit the old one's data, but the Layer 1 native files keep running underneath either way. Layer 3 - what the community builds beyond the official 8. Two flavors. Some community projects are MemoryProvider plug-ins that compete head-to-head with the Layer 2 picks (Mnemosyne is the standout - fully local, sub-millisecond, with a real tiered cognitive architecture). Others sit alongside the official providers in a different slot entirely (GBrain is the standout here - it stores world facts like people, companies, and projects in a markdown vault, while your Layer 2 provider handles operational memory). Layer 3 usually means more setup and less polish than the official 8, but it's where you go when you need a capability the eight providers don't offer. The layers stack rather than replace each other. Switching the Layer 2 provider does not wipe Layer 1. Each provider has its own store, but the native session database and the two markdown files keep running underneath. Layer 3 plug-ins are additive on top of both. ![Hermes Agent memory as a three-layer stack: native memory, official MemoryProviders, and community plug-ins](/guide/memory/assets/hermes-memory-three-layer-stack.jpg) ## Layer 1: Native - what you get out of the box The native layer is three things that ship with every Hermes install: two small markdown files and one database. They play different roles, and it's worth understanding each before we get to the plug-in providers. Note: if you already understand the out of box setup or want to skip to the optional stuff you can install on top, go to Layer 2. ## The two markdown files When you install Hermes, it creates two text files in your home directory at ~/.hermes/: MEMORY.md - the agent's general knowledge notebook. Project context, technical decisions, things worth remembering across sessions. Capped at about 2,200 characters, roughly a paragraph and a half. USER.md - what the agent knows about you specifically. Your preferences, your working style, your role. Capped at about 1,375 characters, roughly one paragraph. You can open both files in any text editor. They're plain markdown. You can even edit them by hand if you want, and the agent will read your edits next session. The reason they're so small is that they aren't the agent's filing cabinet - they're the agent's sticky notes. At the start of every session, Hermes pastes the entire contents of both files into the prompt sent to the model. So everything in these files is always "in front of" the agent. No retrieval needed, it just sees them. The agent itself decides what goes into these files. When something important comes up in a session - you say "I prefer bullet points instead of paragraphs" or the agent figures out that you use Vercel for deployments - the agent calls a tool called memory with one of three actions: add, replace, or remove. There's no read action because the files are already pasted into the prompt; the agent reads them by virtue of looking at its own context. ## What happens when the files fill up? This is where most third-party write-ups get things wrong. They claim Hermes automatically consolidates the files when they hit 80% of the cap. I went into the code at agent/memory_manager.py to verify, and the actual behavior is more interesting: There is no automatic consolidation - the 80% rule is a prompt instruction, not code. The system prompt header shows the agent a real-time fill gauge - something like "MEMORY: 1,847/2,200 chars (84 percent)" - along with the instruction "when memory is above 80% capacity, consolidate entries before adding new ones." The agent reads that, and the agent decides whether to act on it. If the file is already at the cap and the agent tries to add anything anyway, the memory tool returns an error listing the current entries and forces the agent to free space via replace or remove first. This is a deliberate design choice. Nous trusts the model to manage its own notebook. The upside is full agent control, but the downside is also full agent control. A poorly-prompted agent can sit at the cap indefinitely, refusing every new add call and quietly losing information that should have replaced something older, but I'm confident this gets resolved soon as there's some PRs around this. A related point of confusion worth clearing up before we go on: v0.12 introduced something called the "Autonomous Curator" and many write-ups describe it as automatic memory management. It is not. The Curator operates only on the agent's skill library at ~/.hermes/skills/ - moving skills from active to stale to archived based on usage. It never touches MEMORY.md or USER.md. ## The database (and how it relates to the markdown files) The two markdown files are the agent's always-visible notes. The database is the agent's full archive of everything that has ever happened. Hermes stores every session in a SQLite database file at ~/.hermes/hermes_state.db. Every user message, every agent response, every tool call, every reasoning step, plus economic data like token counts and dollar cost per session - all of it lands here. Default retention is 90 days; older sessions get pruned automatically every 24 hours unless you change the setting. This database is not auto-injected into prompts. It would be enormous - imagine pasting your entire chat history into every new conversation. Instead, the agent searches it on demand when it needs to find something specific. The search uses SQLite's built-in full-text search (FTS5), and Hermes maintains two parallel indexes: one for normal word-level search ("did we discuss the content strategy?") and one for trigram search that handles substrings and code tokens ("find every session where I mentioned github"). So the mental model is: The two markdown files = what the agent always has in its head. Small, curated, always present in every prompt. The session database = what the agent can look up if it knows what to look for. Huge, raw, searchable on demand. These are complementary, not redundant. When something matters across all future sessions, the agent should write it to MEMORY.md so it's always present. When something might matter again but doesn't need to be top-of-mind, it lives in the session database and gets pulled up only when the agent searches for it. A nice side-effect of the database design: because Hermes captures every reasoning step and every tool call with full economic data, the database is also a complete training trajectory if you ever want to export it. This is beyond the scope of this article but something that aligns with my thesis on where the moats are in agents. ## Layer 2: The pluggable "MemoryProvider" system This is the layer that lets you graduate from "small notebook plus searchable archive" to a real memory system - one that extracts facts from your conversations automatically, builds a profile of you, supports semantic recall across sessions, or handles a large knowledge graph. Setting this up is quite simple - you run "hermes memory setup", pick a provider from the menu, and from then on the agent has a richer memory layer to draw from on top of the native files. Note: some providers require API keys and paid plans. The important note is you can only run one provider at a time. Hermes treats this as a single deliberate choice, not a stack of bolt-ons. That keeps your tool surface clean - each provider exposes its own set of agent tools, and the agent would get confused if there were three competing "search memory" tools sitting in front of it - and it makes the configuration easy to reason about. The Layer 1 native files keep running underneath whether you have a provider active or not. Picking the right provider matters because they make very different architectural bets. Some are aggressive at extracting facts. Some build a model of how you think rather than what you said. Some are obsessed with token efficiency. Some are graph-first. The full decision tree is later in this article; the technical mechanics below are for readers who want to know what providers actually plug into. Let's dive in. ## The 8 Official Providers ## [Honcho](/projects/plastic-labs/honcho) (Plastic Labs) - AI-native dialectic user modeling The only provider in the lineup that tries to model how you think, not just what you said. Instead of storing flat facts like "Kevin uses 4-space indents," Honcho runs a multi-step reasoning pass after your conversations to build a profile of your reasoning patterns, preferences, and goals. That profile evolves over time, so the agent gets better at anticipating what you'd want even on topics you've never discussed. It also lets multiple "AI identities" share the same view of you - useful if you run different specialist agents for coding, writing, and strategy and want all of them to know your style. Most-cited favorite in the Hermes Discord (@offendingcommit: "I've tried them all... I freakin' love Honcho."). ## [Mem0](/projects/mem0ai/mem0) - fastest 30-second setup, broadest ecosystem The "just give me memory and stop asking questions" pick. You sign up for Mem0 cloud, paste an API key, and you're done - the provider extracts facts from conversations, deduplicates them, and serves up semantic search automatically in the background. It's also the exclusive memory provider for AWS's Strands Agents SDK, which gives it the widest ecosystem reach in the lineup. In April 2026 Mem0 shipped a "v3" algorithm claiming to leapfrog Hindsight on benchmarks (94.8 on LongMemEval, 91.6 on LoCoMo). ## [Hindsight](/projects/vectorize-io/hindsight) (Vectorize.io) - the benchmark king The first memory system of any kind to publicly cross 90 on LongMemEval (91.4, December 2025). Hindsight thinks about memory as four separate networks - things about the world, things that happened, opinions, and raw observations - and pulls only a handful of high-value facts from each conversation (2 to 5, not one per sentence). When you ask it something, it runs four different retrieval strategies in parallel - keyword search, vector similarity, graph traversal across related entities, and a recency pass - then fuses the results. That's how it gets the best recall accuracy in the published lineup. It's also the only provider with a reflect tool that lets the agent run a reasoning pass over its own memory. That's uniquely valuable if you're running multiple agents on a shared memory bank and you need an orchestrator to synthesize what all of them know. ## Holographic - zero-dependency, fully local, air-gapped The only provider in the lineup that needs no internet, no API key, and no LLM to function. Everything lives in a local SQLite file. It uses a 1991-era technique called Holographic Reduced Representations to do compositional reasoning over facts - you can bind concepts together algebraically and probe for related ones later. Retrieval is sub-millisecond because it's pure local SQL. ## [OpenViking](/projects/volcengine/OpenViking) - tiered filesystem context DB Your memory lives as files in a directory tree on your disk. You can cat them, grep them, edit them by hand. Each piece of stored knowledge has three loading tiers: a one-sentence summary, a paragraph-level overview, and the full content. When the agent recalls something, it starts cheap (summaries only) and only loads the deeper tiers if the summary looks relevant. That structure is important if you're cost-sensitive at scale or you want memory you can read and edit like normal files. ## RetainDB - cheapest paid tier, lowest friction $20/month for 100,000 queries, with a free tier of 10,000 operations to test. The only provider in the lineup that's cloud-only at every price point (no self-host even on enterprise). The hook is convenience: you operate no infrastructure, RetainDB handles everything, and there's a "Memory Router" mode that intercepts your LLM calls and adds memory transparently with one config line. Pick this option if you want shared memory across team members or agents and you don't want to operate a database. ## [ByteRover](/projects/campfirein/byterover-cli) - memory as a git repo Your memory is plain markdown files in a .brv/context-tree/ directory - grep-able, version-controllable, no database to run. ByteRover layers a 5-tier retrieval system on top, and four of those tiers don't need an LLM call, so most lookups finish in under 100ms with zero token spend. The key selling point: you can branch, merge, and roll back memory like code with CLI commands. It also uses a special hook to extract high-value insights before Hermes compresses context, which is the cleanest fix in the lineup for the "agent loses memory after restart" failure mode (noted in issue #17251). ## [Supermemory](/projects/supermemoryai/supermemory) - latency + scale leader Sub-300ms recall sustained at over 100 billion tokens per month. Supermemory built a custom vector graph engine for this rather than stapling a vector DB and a graph DB together. Its standout feature is context fencing: it automatically strips already-recalled memories out of conversations before storing them, which kills the "memory feedback loop" where auto-capture systems start re-ingesting their own outputs into the next round of memory. Good choice if you want to operate at real scale (consumer app, multi-tenant SaaS, agent platform) and latency matters, but likely overkill for normal consumer use. Here's a comparative look across all 8 ![Memory Provider Comparison table for the eight official Hermes MemoryProviders](/guide/memory/assets/memory-provider-comparison.jpg) ## Layer 3: Community plug-ins worth knowing If none of the official 8 fits your use case, or if you want even more on top, the community has built another layer of memory tooling for Hermes. About five of these are production-quality enough to consider seriously, plus a longer tail of experiments to keep eyes on. Two things to know up front about Layer 3: Not every Layer 3 project competes with Layer 2. Some are alternative MemoryProvider plug-ins you'd pick instead of one of the official 8 ([Mnemosyne](/projects/AxDSan/mnemosyne) is the clearest example). Others occupy a different role entirely - they store a different type of memory and run alongside your Layer 2 provider, not in place of it ([GBrain](/projects/garrytan/gbrain) is the clearest example, storing world facts about people, companies, and projects in a separate brain layer while your Layer 2 provider handles operational memory). You give up polish to get capability. The official 8 ship with Nous's review and tend to "just work." Community plug-ins are typically a bit rougher on the install, have fewer docs, and more chance of hitting a bug. But they unlock things the official set doesn't offer like fully-local sub-millisecond retrieval (Mnemosyne), a markdown-and-Postgres knowledge graph that builds itself with zero LLM calls (GBrain), explainable retrieval rankings (yantrikdb), and cross-agent memory portability (PLUR). The safe path if you're committing to a memory stack for real work: start with one of the official 8 and only reach for Layer 3 when you've identified a specific capability gap a community project fills. The standouts below are [GBrain](/projects/garrytan/gbrain) and [Mnemosyne](/projects/AxDSan/mnemosyne). ## [GBrain](/projects/garrytan/gbrain) (by garrytan) - this is what I personally use Open-sourced in April, MIT licensed, ~18k+ stars. TypeScript. Built by Garry Tan to run his own production agents. GBrain is structurally different from the official 8. GBrain does not subclass MemoryProvider, it plugs in as skillpack + MCP server (~30 MCP tools), and occupys a different ontological slot. The explicit doctrine in docs/guides/brain-vs-memory.md: What makes it special: Not just RAG: a full 8-layer knowledge engine for dramatically better memory and recall Epistemology layer: tracks “who said what, when, and with what confidence” so no more hallucinated facts or lost context Self-wiring knowledge graph: automatically extracts entities and creates real relationships (e.g., “attended,” “works_at,” “invested_in,” “founded”) with zero extra LLM calls Dream cycles for autonomous synthesis: runs overnight (or on-demand) so your brain literally gets smarter while you sleep Hybrid search done right: combines vector, keyword, RRF fusion, multi-query expansion, cosine reranking, compiled-truth boost, and backlink boost for far more accurate results than plain vector search Specialized + versioned chunking: recursive markdown chunker (v4) that intelligently handles code blocks, frontmatter, transcripts, etc. so edits don’t break memory Autonomous enrichment + persistent personal memory: tiered enrichment based on how often something is mentioned turning Hermes agent into a “clairvoyant” personal AI that actually knows you Why pick GBrain over the official 8? If you want a graph cheap, git as system of record, overnight maintenance, you already have a markdown vault (migration covers Obsidian / Logseq / Notion / Roam), or you're building a "company of agents." ## [Mnemosyne](/projects/AxDSan/mnemosyne) (AxDSan/mnemosyne) The strongest community alternative when you want a real MemoryProvider plug-in (rather than GBrain, which plays a different role). Runs entirely on your machine - no cloud, no API key, no internet - and recall is fast enough to feel instant (under 2 milliseconds in published tests). What makes Mnemosyne interesting is its tiered memory architecture, modeled loosely on how humans handle short-term vs long-term memory. There's a "working" tier for what's actively relevant right now, an "episodic" tier for time-stamped events you might want to look up later, and a "scratchpad" for things still being considered for promotion. A consolidation pass runs periodically in the background to move useful items into long-term memory and prune the noise. The standout feature for serious users: memory has a sense of time. You can ask "what did I believe about X last Tuesday?" and get back the agent's understanding as it was at that point, not as it is today. No other Hermes plug-in does this as cleanly. One soft adoption signal worth noticing: Mnemosyne is the only community memory plug-in that someone has bothered to write a dedicated Hermes skill wrapper for (a small file that teaches the agent how to use it intelligently). Nobody's done that for the others. ## Others worth knowing about [Ladybug Memory](/projects/Ladybug-Memory/hermes-memory-plugin) - the local-only option with built-in importance ranking. Every memory gets a score from 1 to 10 so the system surfaces the things that matter first instead of treating everything equally. Pick it if you want fully-local memory and the built-in MEMORY.md cap is too small for your knowledge. [yantrikdb](/projects/yantrikos/yantrikdb-hermes-plugin) - the one to pick when you need to know why the agent recalled what it did. Every retrieval comes back with a "why retrieved" explanation, which is useful for debugging when the agent surfaces the wrong thing or for high-trust contexts where you need to audit what's shaping the agent's responses. Runs embedded out of the box, no separate database to manage. [hermes-agentmemory](/projects/MukundaKatta/hermes-agentmemory) - a community fix for a real Hermes problem: when you tell the agent to forget something, it doesn't actually forget - it keeps an internal summary that quietly influences future recall. This provider does real deletion (gone is gone) and logs every memory operation so you can audit what happened. Pick it if compliance, privacy, or user-controlled forgetting matters. [PLUR](/projects/plur-ai/plur) - the cross-agent memory bridge. Hermes memory normally doesn't reach Cursor, and Cursor's doesn't reach Claude Code. PLUR stores everything in a shared .plur/ folder that all of them can read, so a fact you teach one agent automatically shows up in the others. Pick it if you work across multiple agents on the same project and don't want to teach each one separately. [FlowState-QMD](/projects/amanning3390/flowstate-qmd) - The "guess what you'll need next" provider. It tries to predict the agent's next likely query and warms up that memory in advance, so by the time the agent actually searches, the result is already cached and responses come back faster. Pick it if your agent does repetitive long-horizon work where the next step is usually guessable from context. One thing I expected to find that doesn't exist: memory-as-skill is effectively a non-pattern. The agentskills.io standard means a "skill" could in principle implement memory. In practice all credible persistent memory flows through the MemoryProvider ABC. Even skills that "do memory" (the Mnemosyne SKILL.md, for instance) are wrappers around plug-ins, telling the agent how to use them. ## How to actually pick? Step 1: pick your layer strategy ![Flowchart for picking a Hermes memory setup: native only, Layer 2 by need, or shared-state plan](/guide/memory/assets/pick-hermes-memory-setup.jpg) Step 2: pick your layer 2 system ![Memory Setup Quick Picks table mapping requirements to providers](/guide/memory/assets/provider-decision-tree.jpg) ## Warning signs you went too heavy: The agent feels noticeably slower. Responses that used to come back in about a second now take 3+ seconds. A heavy memory layer adds work on every turn, and once latency creeps past a few seconds the agent stops feeling responsive. Your API bill is creeping up for the same usage. Memory operations consume tokens, and some providers fire extra background LLM calls every time you save something. If your usage patterns haven't changed but your spend has, suspect the memory layer. The agent starts contradicting itself. It recalls one version of a fact in one session and the opposite in the next, and can't tell you which is right. This usually means memory is accumulating without ever being consolidated - the agent is now drawing from a polluted well. The agent runs out of context mid-conversation. A greedy memory layer eats into the same context budget your actual conversation needs. If you start seeing "context too long" errors, or the agent forgets what you told it five minutes ago, the memory layer is overspending its share. Your work isn't actually getting better. This is the one that matters most. You added memory expecting more accurate, more personalized output. After a couple of weeks, can you point at a specific way the agent is genuinely better than before? If you can't, the memory layer isn't earning its complexity. Pull it. ## Frequently asked questions ## What are the layers of Hermes Agent memory? Hermes Agent memory has three practical layers: native memory that ships with Hermes, one optional official MemoryProvider, and community plug-ins such as [GBrain](/projects/garrytan/gbrain) or [Mnemosyne](/projects/AxDSan/mnemosyne) for specialized needs. ## Which Hermes memory provider should I choose? Start with native memory unless you need semantic recall, shared team memory, graph memory, or compliance-grade deletion. Then choose the provider that matches that specific gap rather than installing memory infrastructure by default. ## Can Hermes Agent use GBrain with another MemoryProvider? Yes. [GBrain](/projects/garrytan/gbrain) occupies a different knowledge-graph slot than the official MemoryProvider layer, so it can complement a Layer 2 provider that handles operational conversation memory. I hope you enjoyed this Hermes Agent deep dive on all things memory. If you want to explore more within the Hermes ecosystem, check out [hermesatlas.com](https://hermesatlas.com) and sign up for the [Hermes Atlas newsletter](/#newsletter) to stay up to date on everything. --- # How to Run Hermes Agent (/guide/modes/) Canonical URL: https://hermesatlas.com/guide/modes/ # How to Run Hermes Agent: Desktop vs CLI vs Docker/VPS vs Bot Gateway The decision guide to every way of running Hermes Agent. Live version: https://hermesatlas.com/guide/modes/ — facts sourced from the official docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR You don't choose a front-end — you choose where the agent lives. Hermes Desktop, the CLI/TUI, and the web dashboard are front-ends to the same agent core: same config, API keys, sessions, skills, and memory. The official docs say "Pick whichever fits the moment. They share state." The real decision is where the agent process runs: your own machine (simplest), a Docker container on a VPS or home server (always-on), managed Hermes Cloud (hosted), or your phone via Termux (best-effort). ## The front-ends - **Hermes Desktop** — native app for macOS, Windows, Linux; same agent core as the CLI ("not a separate product or a lightweight clone"). Best default for most people: multi-session chat windows, Bot Mode roster, Memory Graph, Quick Entry global hotkey, and multi-connection to several remote gateways/VPS/Cloud instances at once. If you run the CLI, `hermes desktop` launches the app against your existing config. - **CLI / TUI** — two terminal front-ends over one SQLite session store. The TUI (`hermes --tui`, Node.js ≥ 20) is officially "the recommended way to run Hermes interactively." Power features: worktree-isolated parallel agents (`hermes -w`), background sessions (`/bg`), shell passthrough (`!cmd`), skill slash-commands. - **Web dashboard** — `hermes dashboard`, a machine-level browser admin panel at 127.0.0.1:9119 managing every profile; for local use no data leaves localhost. Its optional Chat tab embeds the TUI via pseudo-terminal (POSIX PTY — WSL2 rather than native Windows). ## Where the agent lives - **Your machine (default):** install.sh (macOS/Linux/WSL2) or install.ps1/Desktop installer (Windows). Simplest; updates via `hermes update`. The agent sleeps when your laptop does — cron and bots included. - **Docker on a VPS/home server (always-on):** official image `nousresearch/hermes-agent` (x86_64 + aarch64, Tier 1) with s6-overlay supervising gateway + dashboard (auto-restart). One container can host several profiles (now the recommended pattern). Minimum 1GB/1 core; 2–4GB with browser tools. Docker installs do NOT support `hermes update` — pull a new image. Never point two gateway containers at one data dir (session/memory corruption). - **Security on VPS:** binding the dashboard/backend to a non-loopback address engages a mandatory auth gate; `--insecure` is a deprecated no-op. In June 2026 unauthenticated public dashboards were the entry point for a real campaign that planted SSH-key backdoors via MCP-config persistence. Official guidance: OAuth via Nous Portal for anything public; username/password only on a trusted LAN or VPN (Tailscale). - **Managed Hermes Cloud:** hosted instances via portal.nousresearch.com/cloud — create/start/stop/destroy from the Portal or via its MCP server. The convenience path; docs are thinner than Docker's. Desktop connects to Cloud instances like any remote gateway. - **Your phone (Termux, Tier 2):** tested bundle is CLI + cron + background terminal + best-effort Telegram gateway + MCP + memory. Android may suspend background jobs, so gateway persistence is best-effort; voice and full browser bootstrap are unavailable. Most people instead pair a VPS gateway with Telegram on the phone. ## Bots and messaging "Bot mode" is the messaging gateway: one background process connecting to all configured platforms — Telegram, Discord, Slack, Google Chat, WhatsApp, Signal, SMS and 15+ more, each with different feature support (voice/images/files/threads/streaming) per the official platform comparison. `hermes gateway setup` is the entry point from any install mode. In Desktop, Bot Mode is built in and on by default; a bot is a Hermes profile with CLI parity (`hermes -p chat`). ## Platform support tiers (official) - **Tier 1** (fixes take first priority; installs/updates should never break): macOS Apple Silicon, Windows 10/11 native (x86_64 + aarch64), Linux & WSL2, Docker. - **Tier 2** (best effort; releases may break them): Android/Termux, Nix — Nix "breaks often due to node.js packaging woes." - **Unsupported** (may break anytime; PRs not accepted): AUR, Intel Macs, pip/uv tool installs, brew. ## Windows: native or WSL2? Both Tier 1. Pick WSL2 if: you want the dashboard's embedded terminal tab (POSIX PTY, WSL2-only), you do POSIX-heavy development and want Hermes on the same Linux filesystem as your tools, or you already maintain WSL2. Native is fine or better otherwise: chat, gateway, cron, browser tool, and MCP all run natively, and you avoid crossing the WSL↔Windows boundary for files and URLs. ## Recommendations - Just trying Hermes → Hermes Desktop on a Tier-1 machine. - Terminal person → install.sh + `hermes --tui`. - Always-on bot → Docker on a small VPS (or Hermes Cloud), dashboard behind OAuth or a tailnet; manage from Desktop remote connections. - Phone → Telegram against a VPS gateway first; Termux only for phone-local execution. - NixOS → extensive official guide, still Tier 2. ## FAQ **Does Hermes Agent have a desktop app?** Yes — Hermes Desktop for macOS, Windows, Linux; same agent core as the CLI. Install from the official page or run `hermes desktop`. **Desktop or CLI?** Not either/or — they share state. Desktop adds visual multi-session and bot management; the TUI is the officially recommended interactive terminal experience. **Raspberry Pi / home server?** Yes — Docker is Tier 1 on aarch64. 1GB/1 core minimum (2–4GB with browser tools); update by pulling a new image. **Android?** Yes via Termux (Tier 2): CLI, cron, MCP, memory, best-effort Telegram gateway. Android suspends background jobs, so not an always-on host. **Need a VPS for a Telegram/Discord bot?** No — the gateway runs anywhere including Desktop's Bot Mode — but a VPS or Hermes Cloud is right once the bot must outlive your laptop's lid. **Safe to expose the dashboard on a VPS?** Only behind the auth gate: OAuth for public reachability, username/password strictly LAN/VPN. Unauthenticated dashboards were exploited in June 2026; `--insecure` is now a no-op. **Windows native or WSL2?** Native for most; WSL2 for the dashboard's embedded terminal or a real POSIX dev environment. --- # Hermes Desktop: The Complete Guide (/guide/desktop/) Canonical URL: https://hermesatlas.com/guide/desktop/ # Hermes Desktop: The Complete Guide — Install, Features, Plugins The Hermes Desktop guide. Live version: https://hermesatlas.com/guide/desktop/ — facts sourced from the official Hermes Desktop docs. Current release is v0.21.5 (as of 2026-09-24). ## TL;DR Hermes Desktop is not a separate product — it is the same agent as the CLI with a native UI. Official docs: same config, same API keys, same sessions, same skills, same memory; "anything you do here shows up there." Runs on macOS, Windows, and Linux; launches its own backend (a `hermes serve` process) so it never requires separate server setup. Best starting point for most new users. ## Install (macOS · Windows · Ubuntu/Linux) - Fresh install: download from the official Hermes Desktop page. macOS is Apple Silicon only (Intel Macs are officially unsupported); Windows 10/11 x86_64 and aarch64; Linux builds target mainstream glibc distros (the team tests latest Ubuntu). - Already run the CLI? Type `hermes desktop` — the app picks up your existing config, keys, sessions, and skills. Nothing to migrate. On Ubuntu, this route is usually smoother than hunting a distro package. ## Desktop-only capabilities - Multi-session, multi-window chat with live tool activity, drag-and-drop attachments, side-by-side preview rail, queue editing, find-in-transcript. - Bot Mode: a roster of named agent profiles (each bot IS a Hermes profile), on by default, with group rooms and CLI parity (`hermes -p chat`). - Memory Graph, HUD floating mode, Quick Entry global hotkey. - Multi-connection: attach to several backends at once — local agent plus remote gateways on a VPS, home server, or managed Hermes Cloud instances. - Per-session YOLO toggle and a live context-usage meter with token breakdown by category. ## Plugins and skills Desktop uses the same skills, plugins, and MCP servers as every other Hermes surface — there is no separate desktop plugin format. Anything installed for the CLI is live in the app; Bot Mode profiles inherit the same capabilities. Curated picks: the Hermes Skills Hub (hermesatlas.com/skills/); community plugins & extensions in the ecosystem catalog (hermesatlas.com/ecosystem/); memory setups in the Memory Guidebook (hermesatlas.com/guide/memory/). ## Connecting to a VPS or cloud instance "Remote backend" means a `hermes serve` process you keep running on the remote machine (systemd/tmux) — the app attaches to it; it does not start it for you. Non-loopback binds engage the auth gate. Provider guidance from the docs: OAuth (Nous Portal) preferred for anything reachable beyond your own machine (VPS, public host, cloud); username/password only for trusted LAN or VPN (Tailscale — bind to the tailscale IP); never expose a password-protected backend to the open internet. The messaging gateway is a separate long-running process from `hermes serve` — keep both alive on a remote host. ## Known rough edges - Electron download (~114MB) on install/build can hang on throttling networks; recent versions self-heal via a mirror fallback. - macOS TCC permission prompts and Gatekeeper on first run are expected — the backend runs real agent commands; a signing-identity setup reduces the friction. - If a remote host's SSH key changes, Desktop hard-fails ("latches") rather than silently retrying. - It is the heaviest way to run Hermes; the lightest server install is Docker, not Desktop. ## Recent changes (v2026.8.27 line) Consent-gated browsing with your real Chrome profile (Windows close-with-approval flow), the built-in browser in its own OS window, opt-in OS-keychain encryption for secrets (no more per-launch macOS Keychain prompts), fleet profile rail, managed SSH remote-update engine. Prior release: Bot Mode group-room threads and desktop rendering performance work. ## Desktop vs CLI/TUI Same agent, shared state — start in one, resume in the other. Desktop is best at multi-session work, the Bot Mode roster, remote-gateway management, and visual context controls. The CLI/TUI is best at worktree-parallel agents (`hermes -w`), background sessions, shell passthrough, and scripting; the TUI is officially "the recommended way to run Hermes interactively." Choose Desktop if you're new or juggle several agents/machines; choose the terminal if you script your tools. ## FAQ **Is Hermes Desktop different from the CLI?** No — same agent, native UI ("not a separate product or a lightweight clone"). Sessions move freely between app and terminal. **Install on Ubuntu?** Download the Linux build, or run `hermes desktop` if the CLI is installed. **Plugins?** Yes — same skills/plugins/MCP servers as every surface; browse curated skills and community plugins on the Atlas. **Connect to a VPS or Hermes Cloud?** Yes, several at once. OAuth for public reachability; username/password only over LAN/VPN. **Why the macOS permission prompts?** The backend executes real commands; TCC/Gatekeeper gating is expected on first run. --- # Tonbi's Hermes Agent Masterclass (/masterclass/) Canonical URL: https://hermesatlas.com/masterclass/ Skip to content hermes atlas 280·repos hermes·v0.21.5 ★ star this repo home ecosystem lists skills use cases handbook masterclass dev reports source map / masterclass watch · learn · build Hermes Agent Masterclass Ten modules that take Hermes from a fresh install to a hardened multi-agent team. Watch Tonbi build the whole system, then open our transcript-derived field notes for the decisions, shortcuts, and gotchas worth remembering. 10 modules 5h 14m beginner → advanced created & taught by Tonbi's AI Garage Tonbi turns Hermes Agent's fast-moving feature set into practical, screen-level walkthroughs. The videos and teaching are his; Hermes Atlas organized the series and distilled the notes below from his transcripts. YouTube channel ↗ full playlist ↗ follow Tonbi ↗ jump to a module 01 setup 02 deploy 03 memory 04 skills 05 models 06 tools & MCP 07 automation 08 subagents 09 profiles 10 security 01 28:31 · foundations module 01 · start here Installation, setup & basic commands watch on YouTube ↗ Here's what you need to know + the short version Get one clean chat working before you add complexity. Pick a provider, learn the few commands that keep you oriented, and give Hermes a concrete first task whose result you can verify. 02:12 The payoff compounds. Hermes is most useful when repeated sessions build memory and reusable skills. If all you need is an occasional chatbot, the extra machinery may not earn its keep. 06:48 Stabilize the base provider first. Choose a model you can reliably call, then add fallback credentials or routing. Do not debug gateways, tools, and provider auth at the same time. 13:08 Memorize the operator basics. hermes starts chat; hermes gateway starts messaging; hermes doctor checks the install; hermes model reopens model configuration. 16:43 You can steer without restarting. Switch models in-session with /model , compact a long context with /compress , and use background or queued prompts when you do not want to derail the active task. 19:40 Know where state lives. The .hermes directory holds config, environment, memories, sessions, cron, and logs. Tonbi's rule: edit config and memory deliberately; let Hermes manage session and cron internals. 21:26 Test with real work. A bounded research task proves web search, tool calling, and synthesis in one go—and exposes a broken setup faster than a casual “hello.” 02 30:50 · deployment module 02 · run it anywhere VPS, Docker & messaging watch on YouTube ↗ Here's what you need to know + the short version Choose a backend by the blast radius and uptime you need: local for simplicity, Docker for containment, VPS for always-on access. One gateway can then expose the same agent through many messaging apps. 01:06 Backend is an operating decision. Local is easiest, Docker keeps command execution off the host, and a VPS keeps Hermes awake when your laptop is closed. 03:13 Persistence and isolation are separate. Configure the Docker backend so the sandbox keeps the files it needs between turns without handing it your whole host filesystem. 09:37 Make an always-on host survive logout. Use SSH key authentication and install the gateway as a supervised service; enable linger when needed so the user service stays alive after SSH disconnects. 14:53 The gateway is one room with many doors. Telegram, Discord, and the CLI can feed the same agent, memory, sessions, and skills. You do not need a separate Hermes install per channel. 15:55 Treat bot tokens like passwords. Create the Telegram bot through BotFather, restrict who may talk to it, and never paste the token into prompts or public config. 17:40 Discord's easy-to-miss step is intents. Enable the required message-content intents in the developer portal; skipping them produces a bot that connects but receives empty messages. 03 34:20 · memory module 03 · make context compound Memory, Honcho & Obsidian watch on YouTube ↗ Here's what you need to know + the short version Hermes memory is intentionally layered. Keep the tiny built-in files curated, search old sessions only when needed, add one provider for richer recall, and use an Obsidian vault for project-scale knowledge. 01:30 The small cap is a feature. memory.md and user.md share a tightly bounded prompt budget, forcing Hermes to retain durable preferences, facts, corrections, and conventions instead of a junk drawer. 06:00 Memory writes appear next session. Disk updates immediately, but the system prompt stays frozen for the current session so prompt caching remains useful. A same-session test can therefore look “forgotten” even when the write succeeded. 12:00 Session search is the deep archive. FTS5 lets Hermes retrieve an old conversation on demand without paying to keep every session in the active prompt. 15:00 Run one provider at a time. Honcho, Mem0, Hindsight, and SuperMemory augment the built-in layer; switching providers does not migrate the memory you accumulated in the previous one. 21:00 Provider choice is about memory shape. Honcho emphasizes a modeled understanding of the user; other providers lean toward extraction, knowledge graphs, or partitioned containers. Pick the behavior you actually need. 26:00 Obsidian is a skill, not a provider. Use it for structured, long-form project knowledge that would overwhelm the built-in cap. Point the skill at a vault path and let Hermes create linked Markdown files. 04 41:19 · skills module 04 · procedural memory Skills that grow with the agent watch on YouTube ↗ Here's what you need to know + the short version A skill is a reusable instruction package. The description gets it selected, the body teaches the procedure, and the Curator keeps custom skills from turning into an unmaintained pile. 02:00 SKILL.md is the unit. Front matter names and describes the skill; the body contains the workflow. References, scripts, templates, and assets are optional supporting material. 04:00 The description is the picker hint. Hermes sees names and descriptions before it reads a body. A vague description means the right skill may never load, no matter how good its instructions are. 05:30 Progressive disclosure keeps context lean. Hermes can carry a large catalog because only the selected skill body enters the prompt; everything else stays on disk. 23:00 Install narrowly and inspect sources. Prefer bundled or trusted hub skills, let the security scan run, and use /reload skills to pick up changes without restarting the whole agent. 25:30 Agent-written skills are procedural memory. When a complex tool sequence works, capturing it as a skill makes the next run faster and more consistent than rediscovering the steps. 31:00 Pin what must not drift. The Curator grades and consolidates custom skills; pin a business-critical workflow so automated housekeeping cannot rewrite or archive it. 39:00 Know skill versus plugin. If you are teaching knowledge or a repeatable procedure, use a skill. If you are adding executable product surface, backend routes, or UI, build a plugin. 05 25:20 · models module 05 · spend intelligence wisely Providers, models & local inference watch on YouTube ↗ Here's what you need to know + the short version Use an expensive model where judgment matters and cheaper models everywhere else. Hermes separates providers, credentials, fallbacks, and auxiliary tasks so cost control does not require giving up a strong primary agent. 01:12 Provider and model are different decisions. The provider controls authentication, billing, and transport; the model controls capability, context, and price. 05:21 Tier the work. Put routine title generation, session search, compression, and other auxiliary jobs on inexpensive models. Keep a better default or specialist model for tasks where mistakes cost more. 10:16 Credential pools are resilience, not just billing. Rotate keys when one hits a rate limit; cron jobs and subagents inherit the pool automatically. 12:25 Manual switching stays useful. Hermes does not offer arbitrary per-skill or complexity-based routing. Use /model mid-session when you know the next phase deserves a different model. 13:38 Local tool calling needs the right server flags. In Tonbi's llama.cpp setup, quantized KV cache and flash attention make the model fit; the Jinja chat template is the easy-to-miss requirement for tools. 17:32 Ollama's context default can break agents. Set a sufficiently large context length before blaming Hermes for truncated plans or failed tool loops. 20:04 Hermes Proxy makes subscriptions reusable. It exposes a local OpenAI-compatible endpoint backed by your configured OAuth provider, so compatible tools can share that access without receiving the real credential. 06 26:16 · tools module 06 · give the model hands Tools & MCP servers watch on YouTube ↗ Here's what you need to know + the short version The model requests; Hermes executes. Keep that boundary explicit, expose only the tools a task needs, and treat every MCP server as new code entering the agent's trust surface. 03:04 A tool has three pieces. The function does the work, the schema tells the model when and how to call it, and the registry makes it available. The model never executes the function directly. 04:00 Design the failure shape. Return a clean, structured error so the model can recover, choose another tool, or ask for missing input instead of crashing the whole turn. 05:01 Prefer structured tools over shell improvisation. Purpose-built file, search, and patch tools are easier to audit and give the model a clearer recovery path than a chain of opaque shell commands. 06:56 Scope and sandbox answer different questions. Tool sets decide what the agent can reach; local, Docker, or SSH backends decide where execution happens. 10:00 Use the safe set for untrusted work. Read-only research and media tools without file writes or shell access are a better default for public-facing or research-only agents. 12:12 Do not connect every MCP tool. Add the right server, filter it to the smallest useful surface, prefer OAuth to copied long-lived tokens, and let package scanning inspect local launchers. 21:28 Build a native tool for repeated, stable capability. A small API-backed function with a precise schema is a good fit when the agent should recognize and call the same operation automatically. 07 35:55 · automation module 07 · remove yourself from the loop Cron & automation watch on YouTube ↗ Here's what you need to know + the short version A good cron job is a self-contained runbook, not a reminder to an agent that remembers yesterday. Use scripts for free polling, wake the model only when judgment is needed, and pass upstream output directly into downstream jobs. 02:19 Cron lives in the gateway. The always-on gateway checks the schedule and creates a fresh, isolated session for each run. 06:21 Runaway self-scheduling is blocked. A cron execution cannot create more cron jobs, preventing a job-spawns-job loop from multiplying unnoticed. 09:10 Use silent for healthy states. Monitoring jobs can suppress routine “all good” deliveries while failures still surface. 11:18 Fresh sessions know nothing about “that issue.” Include the host, path, command, expected state, delivery target, and success/failure behavior in the job prompt. 12:39 no_agent is the zero-model path. If a deterministic script can collect or check the state, let it run alone rather than spending tokens on narration. 14:50 Put a cheap gate before expensive judgment. A pre-run script can return “wake agent: false” until something changes, then hand the changed state to the model for triage. 25:30 context-from is enough for many pipelines. Feed the latest completed output of one or several jobs directly into the next prompt; this removes file-path bookkeeping and extra tool calls. 08 33:27 · delegation module 08 · parallelize the right work Subagents & delegation watch on YouTube ↗ Here's what you need to know + the short version Delegate independent, messy work that benefits from a clean context or parallel execution. Brief each child like a stranger, keep its tools narrow, and reserve the stronger model for orchestration and final judgment. 02:21 Delegation solves context poisoning and serial slowness. Tool traces and false starts stay in the child's clean room; only the final summary returns to the parent. 09:07 Subagents know nothing. “Fix the error” is not a brief. Include the exact failure, files, project root, environment, constraints, and definition of done. 10:00 Give each child the least surface it needs. Research may need only web; review may need only read access. Children cannot exceed the parent's tools and leaf children are blocked from sensitive shared operations by default. 11:12 Use cheap children and a strong parent. Route token-heavy collection to one inexpensive delegation model, then let the primary model synthesize short summaries. 13:30 Concurrency is bounded. The default batch is three; larger batches error rather than silently queueing. If the parent is interrupted, synchronous children are canceled too. 20:47 Depth multiplies spend. Children cannot recurse by default. Orchestrator roles and higher spawn depth are opt-in because three branches across three levels can become 27 leaves. 22:00 Background is not durable. background=true lets a child outlive the current turn, but not the session. Use cron or a durable workflow when the work must survive restart. 23:00 Do not delegate tightly dependent work. Keep short, sequential, interactive tasks in one loop; use a script for deterministic mechanics and cron for scheduled or durable work. 09 31:05 · orchestration module 09 · build a durable team Profiles & Kanban watch on YouTube ↗ Here's what you need to know + the short version A profile is a whole persistent Hermes, not a temporary helper. Give each role its own state and model, contain its filesystem separately, then use Kanban when work must cross agents and survive restarts. 02:58 One profile means one isolated Hermes home. It has its own config, model, memory, skills, sessions, cron, logs, gateway, and persona. Two concurrent agents must not share one home or SQLite state will collide. 13:21 Each gateway needs its own bot token. Several profiles can run messaging gateways on one machine, but Hermes blocks a second process from claiming a token already in use. 16:15 Profiles isolate state, not your disk. A local-backend profile can still read the host filesystem. Pin its working directory and use Docker or SSH when you need a real boundary. 17:34 Profiles are portable. Export and import can package the agent's configuration, skills, cron, MCP setup, and persona as a reusable distribution. 18:48 Use Kanban for durable cross-agent work. Subagents fit a task you watch finish in one session; the SQLite-backed board survives gateway restarts and lets a human comment, block, or unblock mid-flight. 20:00 Routing reads descriptions, not names. Write each profile's one-line role precisely. The decomposer builds the task graph, then the router assigns tasks to the profile whose description fits. 21:00 Workers update the board through gated tools. They show, create, complete, block, and comment through the Kanban tool set rather than shelling into the database. 23:00 Model choice follows the assignee. There is no per-card override; route a task to a different profile when it needs a different model or tool surface. 10 27:38 · security module 10 · defense in depth Security watch on YouTube ↗ Here's what you need to know + the short version There is no fully capable, fully safe agent. Start with who can reach it, then layer approvals, containment, secret filtering, injection defenses, network controls, and per-profile least privilege. 02:05 Capability and safety move against each other. Tune the system for its real trust level—a private laptop, a team service, and a public gateway should not share one security posture. 05:00 The gateway fails closed. Configure explicit platform or global user allowlists. With no matching permission, a message never reaches the agent. 07:51 Pick approvals deliberately. Manual asks on risky commands, smart mode lets an auxiliary model approve clear low-risk actions and escalate uncertainty, and YOLO skips almost every prompt. Approval timeouts deny by default. 11:26 YOLO still has a floor. Obvious system-wiping commands are rejected before the approval layer and have no agent-side override. If an operation is truly that destructive, do it manually outside the agent. 13:20 Containment limits the blast radius. Local execution leans heavily on approvals; Docker can sacrifice a container instead of the host. Anything you explicitly mount or forward into that container is still readable and exfiltratable. 17:23 Secrets and instructions are filtered before the model sees them. MCP subprocesses receive a stripped environment, known token patterns are redacted, and prompt-bearing files are scanned for injection and exfiltration patterns. 19:00 Network controls matter too. SSRF protection blocks private and link-local ranges and rechecks redirects; use the shared website blocklist, and only allow private URLs when a trusted local service genuinely requires it. 20:08 Tirith catches what simple patterns miss. Its pre-execution scan looks for homoglyph domains, pipe-to-interpreter commands, and terminal injection tricks. 22:00 Apply least privilege per profile. A researcher can have a domain blocklist and safe tools; a coder can run inside Docker with manual approvals; a low-risk writer may need far less friction. About these notes: Hermes Atlas distilled each module from Tonbi's YouTube description and auto-generated English transcript, then linked every takeaway back to the relevant timestamp. They are editorial summaries, not verbatim transcripts. Hermes Agent changes quickly, so verify version-sensitive commands and feature counts against the current official documentation ↗ . hermes atlas · curated by ksimback · suggest a repo · privacy v2 · 2026.07 --- # State of Hermes — April 2026 Canonical URL: https://hermesatlas.com/reports/state-of-hermes-april-2026 Skip to content hermes atlas 280·repos hermes·v0.21.5 ★ star this repo home ecosystem lists skills use cases handbook masterclass dev reports source map / reports / state of hermes — april 2026 community report · q1 2026 The state of Hermes Agent — April 2026 A community report on the first six weeks of Nous Research's self-improving AI agent. Published apr 11, 2026 · 10 min read · hermesatlas.com TL;DR Six weeks ago, Nous Research quietly released Hermes Agent — an open-source AI agent built around a single contrarian premise: what if your AI got smarter the more you used it, instead of resetting at the end of every session? The community noticed. The repo went from 0 to 57,200 GitHub stars in six weeks, growing faster than OpenClaw at the same stage. But star counts only tell part of the story. The real signal is what's been built around it. In just six weeks, the community has shipped: 3 official Nous Research extensions (autonovel, hermes-paperclip-adapter, hermes-agent-self-evolution) 17 community skill libraries (including the 4,132-star Anthropic Cybersecurity Skills collection mapped to MITRE ATT&CK) 8 external memory providers (Honcho, Mem0, Hindsight, Supermemory, and others) 9 multi-agent orchestration frameworks (mission-control alone has 3,875 stars) 7 deployment templates spanning Docker, Nix, systemd, and managed cloud 80+ quality-filtered repos in total , growing at roughly 5,000 GitHub stars per week ecosystem-wide This report unpacks how a model-research lab from upstate New York turned an open-source release into a movement, what Hermes does differently from OpenClaw and Claude Code, and what to watch for in Q2. newsletter · free · 1–2× / month subscribe 1. What Hermes Agent actually is Hermes Agent is an autonomous AI agent that lives on a server (or your laptop, or a $5 VPS) and gets more capable over time. Three things make it different from every other AI agent framework released in the last two years: 1. A built-in learning loop. When Hermes completes a complex task — say, debugging a microservice or refactoring a Rust crate — it can synthesize that experience into a permanent skill document. These skills follow the agentskills.io open standard: structured Markdown with metadata, written in natural language, callable as slash commands. Next time the agent encounters something similar, it doesn't start from zero. It loads the relevant skill and gets to work. 2. Persistent multi-level memory. Hermes maintains a bounded MEMORY.md (the agent's notes) and USER.md (user profile) that always live in the system prompt. Below that, every session is stored in SQLite with FTS5 full-text search, so the agent can recall any past conversation. Above that, eight pluggable external memory providers (Honcho, Mem0, Hindsight, Supermemory, RetainDB, ByteRover, OpenViking, Holographic) handle long-term semantic memory and graph-based recall. This three-layer architecture is the defining technical decision of the project. 3. A unified gateway across 14 messaging platforms. A single Hermes instance can run as a Telegram bot, a Discord bot, a Slack app, a WhatsApp client, a Signal contact, an SMS endpoint, an Email auto-responder, a Matrix integration, a Mattermost bot, and more — all from the same daemon, with one shared session and one shared memory. You can start a conversation in CLI and continue it in Telegram, then ask it to send the result to your team in Slack. The core repo is MIT-licensed Python (~9,200 lines in run_agent.py alone), supports 20+ LLM providers (OpenRouter, Nous Portal, Anthropic, OpenAI, Gemini, local Ollama, vLLM, etc.), and runs on six execution backends from local processes to Daytona cloud sandboxes. 2. The launch timeline February 25, 2026: Nous Research drops Hermes Agent on GitHub with a simple tweet: "Meet Hermes Agent, the open source agent that grows with you." The launch post gets 557 likes — strong but not viral. February 26-March 10: Tech press picks it up. MarkTechPost runs a piece framing it as a fix for "AI forgetfulness." Bitcoin News crosses the crypto/AI divide with an explainer. The Top AI Product blog calls it "the open-source AI agent that finally remembers everything." March 11: Hits 22,000 GitHub stars and 242 contributors — this would have been a great six-month number for most projects. March 15-25: The skill ecosystem explodes. Vercel Labs publishes their official vercel-labs/agent-skills library. Black Forest Labs (the FLUX image gen team) ships official Hermes-compatible image generation skills. Anthropic releases a 754-skill cybersecurity collection mapped to MITRE ATT&CK, NIST CSF 2.0, and D3FEND. March 23: Nous Research ships v0.4.0 — what Teknium calls "the platform expansion release." 200+ bug fixes, 6 new messaging adapters (Signal, DingTalk, SMS, Mattermost, Matrix, Webhook), MCP server management with OAuth 2.1, an OpenAI-compatible API server, and gateway prompt caching. The release is built from 300 PRs in five days. April 3: Anthropic blocks OpenClaw from accessing Claude Code subscriptions. The Hacker News thread reaches #1 with 1,064 points and 811 comments. Nous Research immediately tweets: "If you're having trouble with your lobster-themed agent since the recent update, try downloading Hermes Agent, then running 'hermes claw migrate'. We've been told this helps a lot." The cheeky migration tool tweet picks up 813 likes. Migration traffic spikes. April 8: v0.8.0 ships with 209 PRs and 82 issue closures. Headline features: live model switching mid-session, free Xiaomi MiMo v2 Pro via Nous Portal, native Google AI Studio (Gemini) integration, Matrix tier-1 support, MCP OAuth 2.1 with PKCE plus OSV malware scanning, and the long-awaited notify_on_complete for background tasks. Manim skill ships the same week and goes viral after Shopify CEO Tobi Lütke uses it to generate a 3Blue1Brown-style math animation in one prompt. April 11: 57,200+ GitHub stars , 7,572 forks, 274 contributors. The ecosystem map at hermesatlas.com now tracks 80+ community projects. Nous Portal partnerships announced with MiniMax (M2.7) and Xiaomi (free MiMo v2 Pro for two weeks). Paradigm + a16z confirmed as Nous Research's lead investors. That's six weeks. 3. Growth in numbers Metric As of April 11, 2026 GitHub stars (core repo) 57,200 Forks 7,572 Contributors 274+ Issues closed 800+ Releases 8 (v0.1 → v0.8) Messaging platforms 14 Community ecosystem repos 80+ External memory providers 8 Total ecosystem stars 90,750 Growth velocity: Roughly 9,500 stars per week on the core repo over the last 30 days. For context, OpenClaw (which had a multi-month head start) is currently growing at ~3,000 stars per week. Hermes Agent has flipped OpenClaw on weekly star growth. Contributor profile: Teknium (Nous Research co-founder) leads the commit count with 179 PRs in v0.8 alone. Top community contributors include @SHL0MS , @alt-glitch , @benbarclay , @CharlieKerfoot , and @WAXLYY . Fourteen distinct contributors merged PRs in the v0.8 release window — a healthy bus factor for a six-week-old project. International reach: Coverage has expanded well beyond English-language tech press. Chinese AI developer @wangray published a deep technical analysis of Hermes's 4-layer memory system that picked up 258 likes and 49,000 views. Japanese developers have shipped install tutorials. The Chinese AI community has noted Nous Research's Web3 connections (Paradigm + a16z) as a sign of credible long-term backing. 4. The three-way positioning: Hermes vs OpenClaw vs Claude Code A fair comparison matters here, because the community keeps trying to frame this as a winner-takes-all competition, and that's not really what's happening. Dimension Claude Code OpenClaw Hermes Agent Core identity Pair-programmer in your IDE Operations platform for teams Personal assistant that learns Architecture IDE-integrated Gateway control plane (Node.js) Runtime AIAgent loop (Python) Memory model Auto-notes to disk Unbounded Markdown Bounded curation + SQLite FTS5 + 8 provider plugins Skills Static, human-authored Static (5,700+ on ClawHub) Autonomously created + refined by the agent Channels IDE only 22+ including iMessage, IRC, LINE 14 including Matrix, DingTalk, Feishu License Proprietary MIT MIT Stars N/A (Anthropic product) ~250,000 57,200 Execution Local sandbox Local Local + Docker + SSH + Modal + Daytona + Singularity Where each one wins: Claude Code wins for focused coding sessions in an IDE. It's the best in-editor pair programmer Anthropic could build, and it integrates deeply with VS Code, Zed, and JetBrains. If you want an AI that helps you write code in your editor, this is the answer. OpenClaw wins for team operations and channel breadth. With 22 channel integrations and a 5,700-skill marketplace, it's the most mature option for running a single agent across an entire company's communication surface. The gateway-first architecture is a strength for ops workflows. Hermes Agent wins for the learning loop and long-horizon work. If you want an agent that gets better at your specific workflows over time — that remembers your project's quirks, that builds reusable skills automatically, that you can trust to run cron jobs unsupervised — Hermes is currently the only credible option. The community consensus, repeated across Reddit, X, Substack, and the Hermes Agent Discord: they're complementary, not competitive. A typical setup uses Claude Code for IDE coding, Hermes Agent for personal automation and learning, and OpenClaw or Slack-native bots for team-wide ops. 5. The architectural bet that defines Hermes If you read just one section of this report, read this one. Hermes Agent's design embodies a specific bet about where AI agents are going, and that bet differs sharply from its competition. The bet: Memory-bounded, deliberately curated agents will outperform unbounded "remember everything" agents in real-world use, because the constraint forces consolidation and consolidation produces better priors. OpenClaw's memory is unbounded. You can dump anything into it. The agent reads everything every turn. The bet is that more context = better answers. Hermes's memory is strictly bounded : 2,200 characters for MEMORY.md , 1,375 for USER.md . When you hit the limit, you can't just keep adding — you have to consolidate. The agent must explicitly decide what's worth remembering. This is a constraint that forces the agent to develop a working theory of what matters about you and your work, and then refine that theory as it gets new evidence. It's the same bet that LLMs make about attention: you can't attend to everything, so you have to learn what to attend to. Hermes applies that bet at the memory layer. The early evidence suggests it's working. Users consistently report that Hermes "feels different" after 2-3 weeks of use in a way that other agents don't. One r/LocalLLaMA user reported a 40% speedup on repeated research tasks after Hermes auto-generated three skill documents over two hours. Another user — quoted on X by Robert Scoble — said "my Hermes agent spooked me with a very specific detail from a setup I was discussing with it 3 weeks ago." Whether this bet is correct is still an open question. But it's a real bet, and it's the first credible alternative to the "infinite context window" school of thought that has dominated AI agent design for the past two years. 6. Community sentiment Tracking community sentiment across X, Reddit, Substack, Hacker News, and the Hermes Agent Discord (~4,000 builders), three themes dominate: Positive: "The first agent harness that you immediately know was developed by people who have a vast knowledge" — @DataDeLaurier "Much less token hungry" than competitors — repeated across r/LocalLLaMA "Excellent right out of the box" with a "5-minute install" — repeated by multiple users " @NousResearch may have cooked with hermes agent" — @fujikanaeda (retweeted by Nous itself) "Hermes is definitely a better coder, id drop the claw altogether lol" — @teknium Critical (acknowledged honestly): Some users report edge case issues with extended use; one well-known user ( @ksubedi ) returned to OpenClaw after testing Local model performance can be slower than running the model directly through LMStudio (one user reported 1-2 tokens/s through Hermes vs 45 tokens/s native) Setup, while generally praised, was called "more tedious than OpenClaw" by @chrysb in the most-liked critical post The signal-to-noise ratio strongly favors Hermes. Out of dozens of posts I've reviewed, the negative ones are specific and technical (and generally being addressed in releases), while the positive ones tend to be more emotional and broader ("magical," "spooked me," "the future"). 7. The ecosystem map Here's the breakdown of what the community has built around Hermes Agent in six weeks. Numbers reflect star counts as of April 11, 2026. Category Count Top project (stars) Core & Official 6 hermes-agent (57.2K) Skills & Registries 17 Anthropic-Cybersecurity-Skills (4.1K) Memory & Context 6 hindsight (8.4K) Multi-Agent & Orchestration 7 mission-control (3.9K) Workspaces & GUIs 4 hermes-workspace (830) Plugins & Extensions 6 hermes-web-search-plus (21) Deployment & Infra 7 llm-agents.nix (967) Integrations & Bridges 5 hermes-android (38) Developer Tools 9 tokscale (1.7K) Domain Applications 8 DashClaw (204) Guides & Docs 5 awesome-hermes-agent (898) Forks & Derivatives 3 hermes-agent-camel (12) The full quality-filtered, security-reviewed, live-data-updated map is available at hermesatlas.com . The most surprising entries — to me, at least — are the cross-pollinations. Hermes-android puts Hermes on your phone via a Python bridge. Hermes-blockchain-oracle is a Solana intelligence MCP server. Hermes-embodied uses Hermes to fine-tune VLA robotics models on cloud GPUs. Hermes-mars-rover simulates Mars exploration with ROS2 and Gazebo. The fact that the ecosystem is already this diverse six weeks in suggests Hermes hit a real nerve. 8. What to watch for in Q2 Five things I'd watch closely over the next 90 days: 1. The skill marketplace network effect. Hermes ships 40+ bundled skills today. The skills hub (built into the CLI) browses agentskills.io, GitHub taps, skills.sh, and ClawHub. If the rate of community skill creation continues to accelerate, Hermes could have a more curated (smaller, but higher-quality) skill marketplace than OpenClaw's by mid-Q2. The wildcard: whether community skills meaningfully cross over from OpenClaw via the OGP (Open Gateway Protocol) federation that both projects support. 2. The multi-instance enterprise story. Hermes profiles let you run isolated agents per client/project on the same machine. If a few high-profile companies start using this for internal automation (DM Slack bot for engineering, separate Telegram bot for sales, all sharing infrastructure), Hermes becomes a real competitor to enterprise agent platforms. Watch for Hermes to ship per-tenant memory isolation and audit logging in v0.9 or v0.10. 3. The self-improvement narrative becoming measurable. Right now, "the agent that grows with you" is a tagline backed by anecdotal evidence. If Nous Research publishes benchmark numbers showing measurable improvement on repeated task families over time — real numbers, not vibes — Hermes becomes impossible to ignore. 4. The Nous Portal subscription economics. Nous gives away free tier access with promotional codes (AGENTHERMES01) and free MiMo v2 Pro for two weeks. At some point this has to convert to a sustainable subscription business. 5. The "first deletion" moment. Every fast-growing open-source project eventually faces a moment where its community has to decide what to remove from the core. Hermes is approaching this: 47 built-in tools, 14 platforms, 6 backends, 8 memory providers. At some point, things will need to move out of core into optional plugins. How Nous handles this transition — and whether the community trusts them with it — will define the next phase. Methodology: Synthesized from 27 research files including official documentation, GitHub release notes, press coverage, X/Twitter analysis, Reddit discussion, and the awesome-hermes-agent curated list. All 80+ ecosystem repos are independently security-reviewed and live-tracked. Not affiliated with Nous Research. Hermes Atlas is an independent community project. Corrections welcome: open an issue if this was useful, drop a ★ on the atlas repo → explore the ecosystem map → newsletter · free stay in the loop new research, reports, and project drops from across the Hermes ecosystem — 1–2× per month. no spam. subscribe handled by beehiiv · privacy hermes atlas · curated by ksimback · suggest a repo · privacy v2 · 2026.04 --- # Skills Hub (/skills/) Canonical URL: https://hermesatlas.com/skills/ Hand-curated judgment layer over the Skills & Skill Registries category. Updated 2026-08-20, tested against Hermes v0.20.4. ## Best Hermes Skills for Coding Canonical URL: https://hermesatlas.com/skills/for-coding Developers looking for skills or plugins that plan, review, harden, or simplify code changes inside Hermes Agent or Claude Code. Structured methodologies and subagent swarms that turn ad-hoc coding sessions into repeatable, checkpointed workflows — spec-first planning, adversarial code review, and multi-agent simplification passes. - obra/superpowers (plugin) — TOP PICK: The most-starred agentic skills framework in the catalog by two orders of magnitude. If you install exactly one dev-workflow plugin, this is the default. Install: hermes plugins install obra/superpowers --enable Compatibility: Hermes Agent CLI (plugin); also ships as a Claude Code plugin via the official marketplace. URL: https://hermesatlas.com/projects/obra/superpowers - Cranot/super-hermes (skill): Built specifically for Hermes' own Skills Hub syntax rather than ported from Claude Code — teaches the agent to write its own analytical prompts via prism-scan plus seven proven analytical lenses. Install: hermes skills tap add Cranot/super-hermes Compatibility: Hermes Agent native (Skills Hub tap); manual git-clone install also documented for other harnesses. URL: https://hermesatlas.com/projects/Cranot/super-hermes - Sahil-SS9/hermaguard (skill): Three parallel subagents attack code from different angles, then verify findings via sandboxed proof-of-concept execution before reporting VERIFIED or REFUTED — the most rigorous read-only code-review skill in this list. Install: Clone the repo and copy it into your harness's skill directory (pip install . provides its 9 console scripts); no Skills Hub listing yet. Compatibility: Harness-agnostic Agent Skill, Python-backed; works with Hermes, Claude Code, and any agentskills.io-compatible client. URL: https://hermesatlas.com/projects/Sahil-SS9/hermaguard - Sahil-SS9/hermes-simplify-swarm (skill): Three read-only subagents (Hygiene, Clarity, Correctness) with a SAFE/CAREFUL/RISKY tiered approval gate before anything is applied — a safer default than a single autonomous simplification pass. Install: git clone https://github.com/Sahil-SS9/hermes-simplify-swarm.git, then copy SKILL.md and references/ into your harness's skill directory as simplify-swarm/. Compatibility: Harness-agnostic (copy-in SKILL.md); explicitly built for Hermes Agent, also works in Claude Code. URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-simplify-swarm - armelhbobdad/bmad-module-skill-forge (skill): Turns your own repo, docs, and developer discourse into agentskills.io-compliant skills with file/line provenance citations — for teams standardizing internal skills, not consuming someone else's. Install: npx bmad-module-skill-forge install Compatibility: Node.js >= 22, Python >= 3.10, uv required; IDE-agnostic scaffolding tool, not Hermes-specific. URL: https://hermesatlas.com/projects/armelhbobdad/bmad-module-skill-forge ## Best Hermes Skills for Cybersecurity Canonical URL: https://hermesatlas.com/skills/for-cybersecurity Security engineers and red-teamers looking for large, framework-mapped skill packs covering offense, defense, and compliance. Structured skill packs mapping MITRE ATT&CK, NIST, and CVE data into agent-usable procedures for pentesting, forensics, and threat modeling. - mukul975/Anthropic-Cybersecurity-Skills (collection) — TOP PICK: 800+ skills across 29 security domains mapped to MITRE ATT&CK, ATLAS, D3FEND, and NIST — the largest and most-starred security pack in the catalog. Start here before any narrower pentest skill. Install: npx skills add mukul975/Anthropic-Cybersecurity-Skills Compatibility: agentskills.io-compatible clients (Claude Code, Copilot, Codex); installable on Hermes via hermes skills tap add or npx skills add. URL: https://hermesatlas.com/projects/mukul975/Anthropic-Cybersecurity-Skills - handnewb/hermes-cybersec-lab (collection): 2,000+ skills stitched from 7 external repos plus 130+ installable tools (Sigma, YARA, MISP). A deeper turnkey lab than the Anthropic-Cybersecurity-Skills pack, but a heavier multi-repo clone — pick it for a dedicated security profile, not a quick add. Install: git clone https://github.com/handnewb/hermes-cybersec-lab.git, run scripts/clone-all.sh, then copy into ~/.hermes/profiles//skills/cybersecurity-lab/. Compatibility: Hermes Agent native — the README targets ~/.hermes/profiles//skills/ explicitly. URL: https://hermesatlas.com/projects/handnewb/hermes-cybersec-lab ## Best Tools for Discovering & Managing Hermes Skills Canonical URL: https://hermesatlas.com/skills/for-skill-management Users who want to browse, retrieve, evolve, or bulk-install skills at scale rather than add a single-purpose skill. Meta-tools that sit above individual skills — registries, retrieval layers, evolution engines, and large curated skill collections spanning many professions. - armelhbobdad/bmad-module-skill-forge (skill): Turns your own repo, docs, and developer discourse into agentskills.io-compliant skills with file/line provenance citations — for teams standardizing internal skills, not consuming someone else's. Install: npx bmad-module-skill-forge install Compatibility: Node.js >= 22, Python >= 3.10, uv required; IDE-agnostic scaffolding tool, not Hermes-specific. URL: https://hermesatlas.com/projects/armelhbobdad/bmad-module-skill-forge - AMAP-ML/SkillClaw (registry) — TOP PICK: A genuinely different mechanism: runs in the background, deduplicates, and cross-pollinates your skill library across agents, devices, and users instead of just hosting a list. Install: git clone https://github.com/AMAP-ML/SkillClaw.git, run scripts/install_skillclaw.sh, activate the venv, then run skillclaw setup. Compatibility: Standalone Python CLI/daemon; integrates with Hermes, Codex, Claude Code, and OpenAI-compatible APIs — not a drop-in SKILL.md. URL: https://hermesatlas.com/projects/AMAP-ML/SkillClaw - aidevelopers2/remoteopenclaw-mcp (registry): Searches 13,000+ MCP servers and 4,000+ agent skills from the terminal with no API key — the widest single search surface in this category, though it's discovery-only, not an installer. Install: Add remoteopenclaw (npx -y remoteopenclaw) under mcp_servers in Hermes' config; for Claude Code: claude mcp add remoteopenclaw -- npx -y remoteopenclaw. Compatibility: MCP server — any MCP client (Hermes, Cursor, Windsurf, Claude Code) via mcp_servers config. URL: https://hermesatlas.com/projects/aidevelopers2/remoteopenclaw-mcp - willingning-coder/eagle-eye (plugin): Five-layer retrieval (hard triggers, FTS5, synonyms, dense embeddings, RRF fusion) built to solve Hermes' own skill-selection problem once your skills directory gets large — the most Hermes-native entry in this group. Install: git clone https://github.com/willingning-coder/eagle-eye.git, then run python scripts/generate_config.py. Compatibility: Hermes Agent plugin; optional dense-embedding dependencies for the retrieval layers. URL: https://hermesatlas.com/projects/willingning-coder/eagle-eye - wondelai/skills (collection): 62 skills built from 50 named business and design frameworks (Jobs-to-be-Done, the Mom Test, Refactoring UI) rather than generic prompts — a business-strategy layer to sit alongside a coding skill set. Install: npx skills add wondelai/skills --all --global (or pick individual skills, e.g. npx skills add wondelai/skills/jobs-to-be-done --global). Compatibility: skills.sh / agentskills.io-compatible clients including Claude Code and Hermes; also ships Claude Code plugin collections. URL: https://hermesatlas.com/projects/wondelai/skills ## Best Hermes Skills for Design & Diagrams Canonical URL: https://hermesatlas.com/skills/for-design-and-diagrams Users generating diagrams, design prototypes, or image output through agent skills. Skills and tools that turn natural-language descriptions into draw.io diagrams, FLUX-generated images, or full local-first design prototypes. - Agents365-ai/drawio-skill (skill) — TOP PICK: Eleven diagram-type presets plus Mermaid-to-drawio conversion, and the most-starred diagram skill in the catalog — the clear default over hand-rolling diagram prompts. Install: npx skills add Agents365-ai/365-skills -g (or git clone into your skills directory). Compatibility: Runs from a single SKILL.md, no MCP server or daemon (needs the draw.io desktop CLI for rendering); works anywhere agentskills.io skills load, including Hermes. URL: https://hermesatlas.com/projects/Agents365-ai/drawio-skill - black-forest-labs/skills (skill): The one official-vendor entry in this bucket — Black Forest Labs' own FLUX prompting guidelines and API integration patterns, not a third-party reverse-engineering of their docs. Install: npx skills add black-forest-labs/skills (or target one: npx skills add black-forest-labs/skills --skill flux-image-best-practices). Compatibility: agentskills.io spec; also a Claude Code plugin. URL: https://hermesatlas.com/projects/black-forest-labs/skills - nexu-io/open-design (plugin): By far the biggest project in the entire skills category — but it's a full local-first design platform, not a lightweight skill. Install it as prototyping infrastructure, not a five-minute skill add. Install: curl -fsSL https://open-design.ai/install.sh | sh -s hermes (hosted); or self-host via docker compose from the repo's deploy/ directory. Compatibility: Native desktop app (macOS/Windows) plus a CLI; the README explicitly lists Hermes Agent among supported coding-agent CLIs for prototype generation. URL: https://hermesatlas.com/projects/nexu-io/open-design ## Best Hermes Skills for Writing & Content Canonical URL: https://hermesatlas.com/skills/for-writing-and-content Content creators and marketers who want to de-AI-ify prose, pull structured video/platform data, or automate content production. Skills for auditing AI-sounding prose, extracting structured YouTube data, and generating marketing or e-commerce material. - conorbronsdon/avoid-ai-writing (skill) — TOP PICK: Three modes (Rewrite, Detect, Edit) and a 100+ entry tiered word-replacement table — the most mechanically detailed de-AI-ify skill in the category, not a vague 'sound more human' prompt. Install: git clone https://github.com/conorbronsdon/avoid-ai-writing into your skills directory (or install the plugin from its marketplace). Compatibility: README states explicit compatibility with Claude Code, OpenClaw, Hermes, and Cursor. URL: https://hermesatlas.com/projects/conorbronsdon/avoid-ai-writing - ZeroPointRepo/youtube-skills (skill): An explicit, working Hermes install line via the skills.sh hub source — covers YouTube transcript, search, channel, and playlist data in one skill. Install: hermes skills install skills-sh/ZeroPointRepo/youtube-skills/skills/youtube-full Compatibility: Hermes Agent (skills.sh source), OpenClaw, Claude Code, Cursor, and Codex via npx skills add. URL: https://hermesatlas.com/projects/ZeroPointRepo/youtube-skills - jiawood2006/hermes-skills (collection): Four narrow, concrete skills — video transcription, AI-text de-humanizer, local OCR, e-commerce material generation — with correct Hermes-native install commands out of the box. Early-stage, but useful for e-commerce and Chinese-language workflows. Install: hermes skills install jiawood2006/hermes-skills/skills/video-to-text (repeat per skill: de-ai-writer, doc-ocr, ecommerce-material-studio). Compatibility: Hermes Agent native install commands documented directly in the README; portable to other agentskills.io clients via manual copy. URL: https://hermesatlas.com/projects/jiawood2006/hermes-skills ## Best Hermes Skills for Crypto & Agent Payments Canonical URL: https://hermesatlas.com/skills/for-crypto-and-payments Builders wiring agents into on-chain protocols or agent-to-agent payment and dispute-resolution rails. Skills for interacting with smart-contract oracle networks and for structuring agent-to-agent commerce, escrow, delegated permissions, and micropayments. - internet-court/internet-court-skill (collection) — TOP PICK: A genuinely new primitive — a master router plus vendored official protocol skills covering ERC-7710 delegated permissions, x402 payments, and escrow/dispute resolution as one catch-all agent-commerce skill. Install: hermes skills tap add internet-court/internet-court-skill (the README prefers the tap over a direct URL install, which misses bundled reference files). Compatibility: Hermes Agent (tap), Claude Code (plugin marketplace or manual clone), OpenClaw, and Codex. URL: https://hermesatlas.com/projects/internet-court/internet-court-skill - smartcontractkit/chainlink-agent-skills (skill): The official Chainlink team's own oracle-network skills (CCIP, VRF, Data Feeds) — the vendor-authoritative pick for cross-chain or oracle work, versus a community reimplementation. Install: npx skills add smartcontractkit/chainlink-agent-skills Compatibility: agentskills.io spec via the skills.sh CLI; project-level install is the default. URL: https://hermesatlas.com/projects/smartcontractkit/chainlink-agent-skills ## Best Hermes Skills for Personal Ops Canonical URL: https://hermesatlas.com/skills/for-personal-ops Users who want Hermes to manage personal infrastructure — self-hosted services and cross-platform runtime friction. Skills that connect Hermes to personal infrastructure like self-hosted Nextcloud and that smooth over Windows/WSL/Git Bash path and runtime quirks. - adnw-vinc/hermes-nextcloud (skill) — TOP PICK: The only skill in the catalog wiring Hermes directly into a self-hosted Nextcloud over WebDAV/CalDAV/CardDAV — no browser, no third-party sync service, credentials kept in a restricted local .env. Install: git clone https://github.com/adnw-vinc/hermes-nextcloud.git into ~/.hermes/skills/productivity/nextcloud, then run its guided setup script. Compatibility: Hermes Agent native — targets ~/.hermes/skills/ explicitly, with App Password validation for Nextcloud. URL: https://hermesatlas.com/projects/adnw-vinc/hermes-nextcloud - CorsenAI/hermes-windows-runtime-skills (collection): Solves a real, narrow Hermes pain point — deterministic path routing and non-destructive Python runtime selection across Windows, Git Bash, and WSL — with exact hermes skills install commands in the README. Install: hermes skills tap add CorsenAI/hermes-windows-runtime-skills (or install each skill directly, e.g. hermes skills install CorsenAI/hermes-windows-runtime-skills/skills/windows-wsl-file-navigation). Compatibility: Hermes Agent native, specifically for native Windows, Git Bash/MSYS, and WSL environments. URL: https://hermesatlas.com/projects/CorsenAI/hermes-windows-runtime-skills --- # Project Catalog (280 projects) --- ## obra/superpowers URL: https://hermesatlas.com/projects/obra/superpowers GitHub: https://github.com/obra/superpowers Category: Skills & Skill Registries Stars: 305,213 An agentic skills framework & software development methodology that works. Superpowers is a software development methodology for coding agents, built from composable skills and initial instructions that guide agents to use them. Its workflow elicits and presents a specification, creates an implementation plan emphasizing TDD, YAGNI, and DRY, then uses subagents to carry out and review engineering tasks. Highlights: - Skills trigger automatically in supported coding-agent harnesses. - The workflow includes specification, planning, and subagent-driven development. - The README lists installation instructions for multiple coding agents. --- ## NousResearch/hermes-agent URL: https://hermesatlas.com/projects/NousResearch/hermes-agent GitHub: https://github.com/NousResearch/hermes-agent Category: Core & Official Stars: 257,151 Official: Yes (maintained by Nous Research) The self-improving AI agent that grows with you — persistent memory, auto-generated skills, 14 platforms, 6 execution backends Hermes Agent is an AI agent with a learning loop that creates and improves skills, stores and searches knowledge across sessions, and builds a model of the user over time. It supports several model providers, terminal interfaces, messaging platforms, scheduled automations, subagents, and multiple terminal backends. Highlights: - Creates skills from experience and improves them during use. - Supports Telegram, Discord, Slack, WhatsApp, Signal, and CLI. - Includes local, Docker, SSH, Modal, Daytona, and Vercel Sandbox backends. --- ## farion1231/cc-switch URL: https://hermesatlas.com/projects/farion1231/cc-switch GitHub: https://github.com/farion1231/cc-switch Category: Workspaces & GUIs Stars: 148,755 Cross-platform all-in-one manager for Claude Code, Codex, OpenCode, OpenClaw, Gemini CLI, and Hermes Agent CC Switch manages API providers for Claude Code, Claude Desktop, Codex, Gemini CLI, Grok Build, OpenCode, OpenClaw, Hermes Agent, Pi, MiniMax Code, Kimi Code, and Oh My Pi. It also provides one place to manage MCP, Skills, and Prompts, without hand-editing JSON, TOML, or YAML configuration files. Highlights: - Switch API providers in one click. - Manage MCP, Skills, and Prompts in one place. - Available for Windows, macOS, and Linux. --- ## TauricResearch/TradingAgents URL: https://hermesatlas.com/projects/TauricResearch/TradingAgents GitHub: https://github.com/TauricResearch/TradingAgents Category: Multi-Agent & Orchestration Stars: 114,984 TradingAgents: Multi-Agents LLM Financial Trading Framework TradingAgents is a multi-agent framework that models the dynamics of real-world trading firms. It assigns tasks to specialized roles, including analyst, trader, and risk-management roles, and supports dynamic discussions about trading strategies. The README says it is designed for research purposes and is not financial, investment, or trading advice. Highlights: - Uses specialized roles for trading tasks - Agents engage in dynamic strategy discussions - Designed for research purposes --- ## nexu-io/open-design URL: https://hermesatlas.com/projects/nexu-io/open-design GitHub: https://github.com/nexu-io/open-design Category: Skills & Skill Registries Stars: 104,025 Local-first open-source design/prototyping system with coding-agent CLI support including Hermes Agent OpenDesign is a collaborative AI design workspace where teams can start with a brief, create a prototype that follows a design system, share it for feedback, and refine it with an agent. It also supports creating and refining slides, images, and motion graphics, and provides skills, design templates, design systems, and plugins under the Apache 2.0 license. Highlights: - Create and refine interactive web prototypes with a live preview. - Create slide decks, images, and motion graphics. - Includes skills, design templates, design systems, and plugins. --- ## colbymchenry/codegraph URL: https://hermesatlas.com/projects/colbymchenry/codegraph GitHub: https://github.com/colbymchenry/codegraph Category: Developer Tools Stars: 75,362 Local pre-indexed code knowledge graph for Hermes Agent and other coding agents to reduce token usage and tool calls CodeGraph is a local code graph for coding agents, with a CLI that builds a project graph in a `.codegraph/` directory. It can connect to supported agents through an MCP server and automatically update the graph when project files change. Highlights: - Builds a project graph with `codegraph init`. - Auto-syncs the graph when files change. - Connects to agents through an MCP server. --- ## mem0ai/mem0 URL: https://hermesatlas.com/projects/mem0ai/mem0 GitHub: https://github.com/mem0ai/mem0 Category: Memory & Context Stars: 67,824 Universal memory layer for AI Agents — official Hermes Agent memory provider, available as managed cloud or Apache-2.0 self-hosted OSS Mem0 is a memory layer for AI assistants and agents that stores user, session, and agent state to support personalized interactions over time. It is available as a Python and npm library, a self-hosted server, or a managed cloud platform. Highlights: - Supports semantic, keyword, and entity-based retrieval. - Offers SDKs, a CLI, self-hosted server, and cloud platform. - Use cases include assistants, customer support, healthcare, productivity, and gaming. --- ## vectorize-io/hindsight URL: https://hermesatlas.com/projects/vectorize-io/hindsight GitHub: https://github.com/vectorize-io/hindsight Category: Memory & Context Stars: 53,890 Official: Yes (maintained by Nous Research) Agent memory that learns — long-term retain/recall/reflect workflows Hindsight is an agent memory system designed to help agents learn over time, rather than only recall conversation history. It provides retain, recall, and reflect operations, and can be self-hosted or used through Hindsight Cloud. Highlights: - Includes retain, recall, and reflect operations. - Offers Docker, pip, and Kubernetes deployment options. - Supports hosted and local LLM providers. --- ## volcengine/OpenViking URL: https://hermesatlas.com/projects/volcengine/OpenViking GitHub: https://github.com/volcengine/OpenViking Category: Memory & Context Stars: 40,839 Open-source context database for AI agents — official Hermes Agent memory provider using viking:// URIs and tiered L0/L1/L2 loading; 91% token reduction and 43-49% task-completion gain over baseline on LoCoMo10. AGPL-3.0. OpenViking is an open-source context database that organizes an AI agent’s knowledge, memories, and skills in a browsable virtual filesystem using `viking://` URIs. It provides directory summaries and three context layers—abstract, overview, and full details—so agents can assess relevance before loading source content. Highlights: - Organizes resources, memories, and skills as files. - Supports scoped semantic search across directories. - Archives sessions and extracts inspectable Markdown memories. --- ## mukul975/Anthropic-Cybersecurity-Skills URL: https://hermesatlas.com/projects/mukul975/Anthropic-Cybersecurity-Skills GitHub: https://github.com/mukul975/Anthropic-Cybersecurity-Skills Category: Skills & Skill Registries Stars: 35,031 754 structured cybersecurity skills mapped to MITRE ATT&CK, NIST CSF 2.0, ATLAS, D3FEND & NIST AI RMF Anthropic-Cybersecurity-Skills is an open-source library containing 818 structured cybersecurity skills designed for AI agents. The repository maps these skills across six industry frameworks, including MITRE ATT&CK, NIST CSF 2.0, and MITRE ATLAS, following the agentskills.io open standard. Highlights: - Contains 818 structured skills across 34 security domains. - Maps skills to MITRE ATT&CK, ATLAS, D3FEND, and F3 frameworks. - Compatible with over 26 AI platforms. --- ## iOfficeAI/AionUi URL: https://hermesatlas.com/projects/iOfficeAI/AionUi GitHub: https://github.com/iOfficeAI/AionUi Category: Workspaces & GUIs Stars: 33,774 Local open-source cowork app for OpenClaw, Hermes Agent, Claude Code, Codex, OpenCode, Gemini CLI, and other agent CLIs AionUi is an open-source cowork app where AI agents can work with files, write code, browse the web, and automate tasks with user approval. It includes a built-in agent with file access, web search, image generation, and MCP tools, and offers a unified interface for using external agents. Highlights: - Includes 21 built-in professional assistants. - Supports remote access through WebUI and messaging platforms. - Runs on macOS, Windows, and Linux. --- ## topoteretes/cognee URL: https://hermesatlas.com/projects/topoteretes/cognee GitHub: https://github.com/topoteretes/cognee Category: Memory & Context Stars: 32,759 Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine. Cognee turns documents, code, and conversations into a self-hosted knowledge graph that agents can search and reuse across sessions. Its local quickstart builds and queries memory using local extraction and embedding models without an LLM; generated answers require additional LLM configuration. Highlights: - Structures text as entities, relationships, and searchable chunks. - Supports custom data models and ontologies. - Offers plugins and MCP for connecting agents. --- ## supermemoryai/supermemory URL: https://hermesatlas.com/projects/supermemoryai/supermemory GitHub: https://github.com/supermemoryai/supermemory Category: Memory & Context Stars: 31,400 Memory engine and API — official Hermes Agent memory provider with sub-300ms recall sustained at 100B+ tokens/month, custom vector graph engine, context fencing, and byte-level dedupe with 100% prompt-cache discount. Supermemory describes itself as a memory and context layer for AI, with an API for adding memory, RAG, user profiles, connectors, and file processing. Its plugins and MCP server provide persistent memory for supported AI assistants, including Hermes. Highlights: - Extracts conversation facts and handles contradictions and automatic forgetting. - Connectors include Google Drive, Gmail, Notion, OneDrive, and GitHub. - Processes PDFs, images, videos, and code. --- ## garrytan/gbrain URL: https://hermesatlas.com/projects/garrytan/gbrain GitHub: https://github.com/garrytan/gbrain Category: Memory & Context Stars: 31,230 Garry's Opinionated OpenClaw/Hermes Agent Brain GBrain stores explicit facts with their sources, supports corrections and withdrawal, and makes memory available across agents. It starts with keyless storage and keyword retrieval, with optional semantic search, synthesis, and background enrichment; it can also expose a brain over MCP. Highlights: - Stores facts with provenance and supports corrections and withdrawal. - Shares memory across agents; transient task state stays local. - Optional features include semantic search, synthesis, and background enrichment. --- ## nesquena/hermes-webui URL: https://hermesatlas.com/projects/nesquena/hermes-webui GitHub: https://github.com/nesquena/hermes-webui Category: Workspaces & GUIs Stars: 19,190 Hermes WebUI: The best way to use Hermes Agent from the web or from your phone! Hermes WebUI is a browser-based interface for Hermes Agent, with chat, session navigation, and workspace file browsing. The README says it uses the existing Hermes agent and models, and provides controls for profiles, settings, and sessions. Highlights: - Three-panel layout for sessions, chat, and workspace files - Includes a workspace file browser with inline previews - Designed for access through an SSH tunnel --- ## fathah/hermes-desktop URL: https://hermesatlas.com/projects/fathah/hermes-desktop GitHub: https://github.com/fathah/hermes-desktop Category: Workspaces & GUIs Stars: 14,456 Desktop companion app for installing, configuring, and chatting with Hermes Agent Hermes One is a community-maintained native desktop app for installing, configuring, and chatting with Hermes Agent. It uses the official Hermes install script, stores Hermes in `~/.hermes`, and provides a GUI for chat, sessions, profiles, memory, skills, tools, scheduling, and messaging gateways. Highlights: - Uses the official Hermes install script. - Provides a GUI for managing profiles, sessions, skills, and tools. - Available from the project website or GitHub Releases. --- ## EKKOLearnAI/ekko-studio URL: https://hermesatlas.com/projects/EKKOLearnAI/ekko-studio GitHub: https://github.com/EKKOLearnAI/ekko-studio Category: Workspaces & GUIs Stars: 11,556 Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics & channel configuration (Telegram, Discord, Slack, WhatsApp) Ekko Studio is a local-first AI workspace available as a desktop app and self-hosted web console. It supports Hermes Agent, Ekko Agent, and coding-agent integrations for chat, workflows, files, voice, and device tools, with session management and platform-channel configuration. Highlights: - Supports multi-agent chat, group chat, and visual workflows. - Includes session management and usage details. - Ships as a desktop app, npm CLI, and Docker image. --- ## Agents365-ai/drawio-skill URL: https://hermesatlas.com/projects/Agents365-ai/drawio-skill GitHub: https://github.com/Agents365-ai/drawio-skill Category: Skills & Skill Registries Stars: 10,359 Generate draw.io diagrams from natural language descriptions drawio-skill is an Agent Skills-format skill that turns natural language descriptions and sources such as Terraform, Kubernetes, SQL DDL, and codebases into editable .drawio diagrams. It supports incremental synchronization that preserves manual layout, architecture rules enforced in CI, and export to formats including HTML, PowerPoint, Mermaid, and Markdown. It runs through a CLI called diagramctl, with an optional MCP server for MCP hosts. Highlights: - Generates editable .drawio files from prompts and real sources - Incremental sync preserves manual layout and annotations - CLI diagramctl with optional MCP server --- ## plastic-labs/honcho URL: https://hermesatlas.com/projects/plastic-labs/honcho GitHub: https://github.com/plastic-labs/honcho Category: Memory & Context Stars: 7,776 Official: Yes (maintained by Nous Research) Memory library for building stateful agents — the upstream library that the elkimek/honcho-self-hosted Hermes wrapper builds on. Honcho is memory infrastructure for stateful agents, with a FastAPI core service and Python and TypeScript SDKs. It stores messages and events, processes them in the background to update peer representations, and provides APIs for querying context, search results, and natural-language answers. It can be used as a managed service, run locally, or self-hosted. Highlights: - Tracks peers, sessions, and messages over time - Provides Python and TypeScript SDKs - Supports managed, local, and self-hosted use --- ## internet-court/internet-court-skill URL: https://hermesatlas.com/projects/internet-court/internet-court-skill GitHub: https://github.com/internet-court/internet-court-skill Category: Skills & Skill Registries Stars: 7,017 The trust layer for agent-to-agent commerce — natural-language mandates, ERC-7710 delegated permissions, x402 payments, escrow, and dispute resolution as one open, catch-all Agent Skill / Claude Code Internet Court is an open skill designed for agent-to-agent commerce that integrates fragmented contacto protocols into a single lifecycle. It provides a framework for structuring deals, holding funds, and establishing adjudication for dispute resolution. Highlights: - Provides a master router and connector skills - Includes vendored copies of official protocol skills - Adds a verification and dispute resolution layer --- ## outsourc-e/hermes-workspace URL: https://hermesatlas.com/projects/outsourc-e/hermes-workspace GitHub: https://github.com/outsourc-e/hermes-workspace Category: Workspaces & GUIs Stars: 6,758 Native web workspace — chat, terminal, memory browser, skills manager, and inspector panel Hermes Workspace is a comprehensive command center designed to orchestrate AI agents through a unified web interface. It integrates with the vanilla hermes-agent to provide a zero-fork environment for managing chat, memory, and system operations. The platform features a Swarm Mode that utilizes tmux-backed workers for autonomous, role-based task dispatching and a Kanban board for tracking progress. Users can manage over 2,000 skills, browse MCP catalogs, and access a cross-platform PTY terminal from a single dashboard. Highlights: - Swarm Mode with role-based dispatch and tmux-backed workers - Integrated memory browser, skills manager, and MCP catalog - Full workspace file browser with Monaco and PTY terminal --- ## builderz-labs/mission-control URL: https://hermesatlas.com/projects/builderz-labs/mission-control GitHub: https://github.com/builderz-labs/mission-control Category: Multi-Agent & Orchestration Stars: 6,398 Self-hosted AI agent orchestration — dispatch tasks, run multi-agent workflows, monitor spend Mission Control is a self-hosted, alpha-stage control plane for operating and governing AI agents. It provides a local dashboard backed by SQLite to dispatch tasks, track token spend, and coordinate agent runtimes such as Claude Code and OpenClaw. Highlights: - Governs tasks, agent registration, memory browsing, and cost tracking. - Provides Web UI, CLI, MCP server, and REST API interfaces. - Supports local installation via Node.js or deployment using Docker. --- ## 0xNyk/awesome-hermes-agent URL: https://hermesatlas.com/projects/0xNyk/awesome-hermes-agent GitHub: https://github.com/0xNyk/awesome-hermes-agent Category: Guides & Docs Stars: 5,901 Curated list of awesome skills, tools, integrations, and resources for Hermes Agent Awesome Hermes Agent is an independent directory of skills, tools, and resources for the Nous Research self-improving agent. It categorizes community-contributed plugins, memory providers, and integrations using editorial maturity tags ranging from experimental to production. Highlights: - Directory for skills, plugins, and memory providers - Categorizes entries by production, beta, and experimental status - Includes links to official Nous Research core repositories --- ## junhoyeo/tokscale URL: https://hermesatlas.com/projects/junhoyeo/tokscale GitHub: https://github.com/junhoyeo/tokscale Category: Developer Tools Stars: 5,743 CLI tool for tracking token usage from Claude Code, OpenClaw, Hermes, Codex, Gemini, and more Tokscale is a CLI tool and visualization dashboard for monitoring and analyzing token consumption and costs across multiple AI coding agents. Its README lists support for agents including Claude Code, OpenClaw, Codex CLI, Gemini CLI, and Hermes Agent. Highlights: - Tracks token usage and costs across multiple AI coding agents. - Provides a CLI and visualization dashboard. - Supports a range of coding agents and tools. --- ## NousResearch/hermes-agent-self-evolution URL: https://hermesatlas.com/projects/NousResearch/hermes-agent-self-evolution GitHub: https://github.com/NousResearch/hermes-agent-self-evolution Category: Core & Official Stars: 5,571 Official: Yes (maintained by Nous Research) Evolutionary self-improvement using DSPy + GEPA — optimizes skills, prompts, and code Hermes Agent Self-Evolution is a framework for the automatic improvement of Hermes Agent's capabilities. It utilizes DSPy and Genetic-Pareto Prompt Evolution (GEPA) to optimize skills, prompts, and code through reflective evolutionary search. The system analyzes execution traces to propose targeted mutations without requiring GPU training. All evolved variants are subject to strict guardrails, including test suites and size limits, before undergoing human review via pull requests. Highlights: - Optimizes skills and prompts using DSPy and GEPA - No GPU training required; operates via API calls - Strict guardrails including full test suites and size limits --- ## conorbronsdon/avoid-ai-writing URL: https://hermesatlas.com/projects/conorbronsdon/avoid-ai-writing GitHub: https://github.com/conorbronsdon/avoid-ai-writing Category: Skills & Skill Registries Stars: 5,243 Audits and rewrites content to eliminate detectable AI writing patterns avoid-ai-writing is a portable writing skill for compatible AI agents that audits and rewrites English prose for AI-writing patterns. It offers rewrite, detect-only, and in-place editing modes, with optional voice profiles and a bundled detector. Highlights: - Rewrite mode supports up to two editing passes. - In-place editing refuses source code, configuration, and generated data. - Detector can score files or piped text. --- ## sergebulaev/linkedin-skills URL: https://hermesatlas.com/projects/sergebulaev/linkedin-skills GitHub: https://github.com/sergebulaev/linkedin-skills Category: Skills & Skill Registries Stars: 5,188 12 LinkedIn skills following the agentskills.io open standard, for Hermes Agent, Claude Code and Codex: write human-sounding posts, draft comments, audit a draft before publishing, and plan a week of cadence LinkedIn Marketing Skills for Claude Code and Codex is a collection of 12 skills for drafting LinkedIn posts, comments, and replies, reviewing drafts, planning content, and editing profiles. The skills show a draft and wait for approval before publishing; the README also documents installation for Hermes Agent and other tools that read SKILL.md files. Highlights: - Includes 12 LinkedIn-focused skills - Drafts require approval before publishing - Supports installation in Hermes Agent --- ## alchaincyf/hermes-agent-orange-book URL: https://hermesatlas.com/projects/alchaincyf/hermes-agent-orange-book GitHub: https://github.com/alchaincyf/hermes-agent-orange-book Category: Guides & Docs Stars: 5,023 Hermes Agent practical guide — Orange Book series (Chinese language) Hermes Agent 2.0: The Complete Guide is a practical guide to the Hermes Agent framework, published as part of the Orange Book series. It covers self-improvement, memory, skills, integrations, multi-agent orchestration, deployment, and security across 21 sections in six parts, with English and Chinese PDF editions available. Highlights: - Covers Hermes Agent across 21 sections and six parts - Includes English and Chinese PDF editions - Released under the MIT License --- ## campfirein/byterover-cli URL: https://hermesatlas.com/projects/campfirein/byterover-cli GitHub: https://github.com/campfirein/byterover-cli Category: Memory & Context Stars: 4,945 Memory as a git repo (formerly Cipher) — official Hermes Agent memory provider with 5-tier retrieval (4 tiers non-LLM, sub-100ms), brv vc commit/branch/merge versioning over plain markdown context tree. Elastic License 2.0. ByteRover CLI is an interactive REPL and context management tool that provides AI coding agents with persistent memory and a structured context tree. It features a Git-like version control system for managing knowledge through commits, branches, and merges, while syncing data with a cloud platform for team collaboration. Highlights: - Interactive TUI and REPL interface powered by React/Ink - Git-like version control for context tree management - Supports 20 LLM providers and 24 built-in agent tools --- ## rlaope/oh-my-hermes URL: https://hermesatlas.com/projects/rlaope/oh-my-hermes GitHub: https://github.com/rlaope/oh-my-hermes Category: Multi-Agent & Orchestration Stars: 4,234 Coding harness, long-term memory system, optimized subagents, and auto model-routing packages for Hermes Agent oh-my-hermes is an operating layer for Hermes Agent that routes work to skills and model chains by category and runs ready graph nodes in parallel. It includes task-ranked long-term memory with explicit decisions about what to retain, and reports work as verified only after a test, review, or CI gate passes. Highlights: - Runs graph-based tasks in parallel with a separate goal-verification node. - Routes lanes to editable model chains based on work category. - Provides a TUI on Hermes' gateway. --- ## spacering-net/codeg URL: https://hermesatlas.com/projects/spacering-net/codeg GitHub: https://github.com/spacering-net/codeg Category: Workspaces & GUIs Stars: 4,098 Collaborative multi-agent coding workspace that aggregates sessions from Hermes, Claude Code, Codex, OpenCode, and others as a desktop or self-hosted app. Codeg brings multiple AI coding agents into one workspace, where they appear in a shared structured conversation interface. It can import, search, and resume agent histories, hand sessions to another agent, and support cross-agent delegation and queued to-dos in separate worktrees. The README lists desktop, self-hosted server, Docker, mobile, and messaging-app access. Highlights: - Includes 19 agents and supports ACP agents. - Import, search, resume, and hand off agent sessions. - Delegate across agents or queue to-dos in worktrees. --- ## tutti-os/tutti URL: https://hermesatlas.com/projects/tutti-os/tutti GitHub: https://github.com/tutti-os/tutti Category: Multi-Agent & Orchestration Stars: 3,843 Collaborative workspace where people and agents build together Tutti is a real-time shared workspace that connects agents’ context, files, apps, and tasks. It supports connecting existing agents and using existing subscription credits; the open-source version also includes built-in apps. The README describes Tutti · VM as adding features such as group chat and simultaneous editing. Highlights: - Agents can reference shared conversations, files, app outputs, and tasks. - Built-in apps include image generation, design, docs, and presentations. - Tutti · VM supports group chat and simultaneous editing. --- ## mnemosyne-oss/mnemosyne URL: https://hermesatlas.com/projects/mnemosyne-oss/mnemosyne GitHub: https://github.com/mnemosyne-oss/mnemosyne Category: Memory & Context Stars: 3,520 The Zero-Dependency, Sub-Millisecond AI Memory System for Hermes Agents Mnemosyne is a Python memory layer for AI agents, using SQLite and requiring no external services. It offers a Python API, a command-line interface, and MCP support, with integrations documented for several agent platforms. Highlights: - Stores and recalls memories in SQLite. - Supports MCP clients and direct Python use. - Includes CLI commands for memory operations and sync. --- ## agent-of-empires/agent-of-empires URL: https://hermesatlas.com/projects/agent-of-empires/agent-of-empires GitHub: https://github.com/agent-of-empires/agent-of-empires Category: Multi-Agent & Orchestration Stars: 3,384 TUI and web control surface for managing multiple coding agents including Hermes Agent, Claude Code, OpenCode, Codex, Gemini, and others Agent of Empires is a session manager for AI coding agents on Linux and macOS. It provides TUI, web, CLI, and HTTP API surfaces for running agents in persistent tmux sessions, with options including Git worktrees and container isolation. Highlights: - Persistent tmux sessions with agent status detection and notifications - Supports Git worktrees and multi-repository workspaces - Web dashboard includes structured views, terminal access, and diffs --- ## Javis603/token-monitor URL: https://hermesatlas.com/projects/Javis603/token-monitor GitHub: https://github.com/Javis603/token-monitor Category: Developer Tools Stars: 3,362 Real-time token, cost, and rate-limit widget with multi-device sync, reading Hermes Agent state directly alongside Claude Code, Codex, and other CLIs. Token Monitor is a desktop app that displays live token usage and AI tool limits across more than 47 AI coding tools, including Claude Code, Codex, and Hermes Agent. It offers historical usage trends and breakdowns by tool, device, model, session, or project, with multi-device sync and views in the main window, menu bar or system tray, and other desktop locations. Highlights: - Supports token usage, tool limits, and session details. - Provides historical trends and usage breakdowns. - Offers real-time multi-device sync. --- ## liaohch3/claude-tap URL: https://hermesatlas.com/projects/liaohch3/claude-tap GitHub: https://github.com/liaohch3/claude-tap Category: Developer Tools Stars: 3,309 Local trace viewer for inspecting coding-agent API traffic from Hermes Agent, Claude Code, Codex, Gemini, Cursor, OpenCode, and others claude-tap is a local proxy and trace viewer for inspecting API traffic and agent context from AI coding clients. It can run a client through the proxy or listen to local app transcripts, and can export trace sessions as self-contained HTML viewers. Highlights: - Inspect prompts, tool calls, streaming responses, and token usage. - Compare adjacent requests to see changes in context. - Redacts common auth headers before recording traces. --- ## AMAP-ML/SkillClaw URL: https://hermesatlas.com/projects/AMAP-ML/SkillClaw GitHub: https://github.com/AMAP-ML/SkillClaw Category: Skills & Skill Registries Stars: 2,723 Let Skills Evolve Collectively with Agentic Evolver SkillClaw integrates with AI agents to evolve and manage skills from interactions across sessions, agents, devices, and users. It describes merging, deduplicating, improving, and sharing skills, and provides installation instructions for macOS, Linux, and Windows. Highlights: - Integrates with Hermes, Codex, Claude Code, and other agents. - Unifies skills across agents and devices. - Offers a dashboard for skills, validation, versions, and session traces. --- ## wondelai/skills URL: https://hermesatlas.com/projects/wondelai/skills GitHub: https://github.com/wondelai/skills Category: Skills & Skill Registries Stars: 2,508 Cross-platform skills library for Claude Code and agentskills.io-compatible agents Wondelai Skills is a library of 65 agent skills and metaskills compatible with agentskills.io-compliant agents, including Claude Code, Codex, and Cursor. The library provides expert frameworks based on industry style guides and books, alongside guided metaskills that maintain state in a project's docs folder to orchestrate tasks across sessions. Highlights: - Includes 51 expert frameworks and 14 guided metaskills. - Compatible with Claude Code, Codex, and agent-plugins.org specifications. - Maintains session state within the project's docs folder. --- ## moorcheh-ai/memanto URL: https://hermesatlas.com/projects/moorcheh-ai/memanto GitHub: https://github.com/moorcheh-ai/memanto Category: Memory & Context Stars: 2,342 Memory that AI Agents Love! Memanto is a companion agent that manages memories for other agents. It extracts durable knowledge, consolidates duplicates, reconciles conflicting information, applies forgetting policies, and briefs agents with relevant memories. The README says it can run locally or in the cloud and export or import memories using the Open Knowledge Format. Highlights: - Extracts and consolidates memories across agents - Reconciles conflicting information and manages forgetting - Supports memory exchange through the Open Knowledge Format --- ## numtide/llm-agents.nix URL: https://hermesatlas.com/projects/numtide/llm-agents.nix GitHub: https://github.com/numtide/llm-agents.nix Category: Deployment & Infra Stars: 2,185 Nix packages for AI coding agents including Hermes llm-agents.nix provides Nix packages for AI coding agents and development tools, with packages automatically updated daily. The README lists tools including terminal coding agents, desktop applications, and development platforms, with example `nix run` commands for each. Highlights: - Packages AI coding agents and development tools for Nix. - Packages are automatically updated daily. - README provides `nix run` examples for listed tools. --- ## Orkas-AI/Orkas URL: https://hermesatlas.com/projects/Orkas-AI/Orkas GitHub: https://github.com/Orkas-AI/Orkas Category: Multi-Agent & Orchestration Stars: 2,172 Open-source multi-agent AI desktop client — a commander LLM dispatches sub-agents in parallel or series; agents self-evolve via reflection and skill crystallization Orkas is an open-source, local-first desktop app where a Commander plans work and delegates tasks to built-in specialists and supported local agents. Projects retain goals, rules, memory, and files across conversations; to-dos, auto-advance, and scheduled automations help ongoing work continue. Highlights: - Includes 16 built-in specialist agents. - Connects to supported local coding and personal agents. - Keeps conversations, files, and custom agents on your disk by default. --- ## bergside/typeui URL: https://hermesatlas.com/projects/bergside/typeui GitHub: https://github.com/bergside/typeui Category: Developer Tools Stars: 2,159 Build better UI with AI TypeUI is an AI-first platform that provides design skills, UI prompts, design systems, and layout variation guidance to help AI tools generate user interfaces for websites and applications. Its resources work with AI providers that support Markdown files or general prompting, and it connects to a range of coding tools through TypeUI MCP or plugins. Highlights: - Provides design skills, UI prompts, and layout guidance. - Supports AI providers that accept Markdown or general prompting. - Connects to coding tools through TypeUI MCP or plugins. --- ## MemTensor/memmy-agent URL: https://hermesatlas.com/projects/MemTensor/memmy-agent GitHub: https://github.com/MemTensor/memmy-agent Category: Memory & Context Stars: 2,142 Personal AI agent and local memory hub — one shared, fully controlled memory and persistent context across Claude Code, Codex, OpenClaw, and Hermes Agent Memmy is a desktop app and CLI/TUI for local memory and AI-agent tasks. Its Memory Service stores and retrieves information, while its agent features can carry project context between supported tools, including Claude Code, Codex, OpenClaw, and Hermes. Highlights: - Provides a local Memory Service and memory CLI. - Offers a desktop app, CLI, and interactive TUI. - README lists integrations with multiple AI coding agents. --- ## dodo-reach/hermes-desktop URL: https://hermesatlas.com/projects/dodo-reach/hermes-desktop GitHub: https://github.com/dodo-reach/hermes-desktop Category: Workspaces & GUIs Stars: 2,032 A native Mac workspace for Hermes: real SSH, real terminal, real session data. Hermes Desktop is a native macOS companion app that provides a dedicated workbench for managing Hermes Agent without relying on browser wrappers or gateway APIs. It connects directly to a local or remote host via SSH to interact with the real machine-first workflow. The app allows users to manage sessions, Kanban boards, cron jobs, and skills while maintaining the host as the sole source of truth. It is designed to complement the official web dashboard by focusing on direct work and system repair via an embedded terminal. Highlights: - Direct local or SSH connection to Hermes hosts - Native views for sessions, Kanban, skills, and cron jobs - Embedded terminal for direct shell access and system repair --- ## NousResearch/hermes-paperclip-adapter URL: https://hermesatlas.com/projects/NousResearch/hermes-paperclip-adapter GitHub: https://github.com/NousResearch/hermes-paperclip-adapter Category: Core & Official Stars: 2,001 Official: Yes (maintained by Nous Research) Run Hermes as a managed employee in Paperclip company systems The hermes-paperclip-adapter is a bridge that integrates Hermes Agent into the Paperclip company management system as a managed employee. It functions by wrapping the Hermes CLI, parsing raw terminal output into structured transcript entries and clean markdown for the Paperclip UI. This allows the agent to respond to task assignments and issue comments while utilizing its native suite of 30+ tools and persistent memory. The adapter also manages session state, skill synchronization, and multi-provider inference settings directly within the Paperclip environment. Highlights: - Integrates Hermes Agent as a managed employee in Paperclip systems - Parses raw CLI output into structured tool cards and markdown - Supports 8 inference providers including Anthropic, OpenAI, and OpenRouter --- ## jau123/MeiGen-AI-Design-MCP URL: https://hermesatlas.com/projects/jau123/MeiGen-AI-Design-MCP GitHub: https://github.com/jau123/MeiGen-AI-Design-MCP Category: Plugins & Extensions Stars: 1,788 Supports GPT Image 2, Nanobanana & ComfyUI, with a 1,400+ prompt library, carefully crafted hooks and a multi-task orchestration system MeiGen AI Design MCP provides tools for AI assistants to search for visual inspiration and create images and videos. It also supports tasks such as background removal, image upscaling, and product imagery, with connections available through remote OAuth or a legacy local npm setup. Highlights: - Search inspiration and view associated prompts. - Generate images and videos with available models. - Connect through remote OAuth or local npm. --- ## Eynzof/Hermes-CN-Desktop URL: https://hermesatlas.com/projects/Eynzof/Hermes-CN-Desktop GitHub: https://github.com/Eynzof/Hermes-CN-Desktop Category: Workspaces & GUIs Stars: 1,713 Windows-first Chinese desktop app for Hermes Agent built with Tauri, TypeScript, and Rust Hermes Agent CN Desktop is a desktop client for the Hermes Agent Chinese community, built with Tauri v2, Rust, React, and TypeScript. It provides a native interface for Windows and macOS to manage the Hermes-CN-Core agent runtime, local processes, and model service configurations. Highlights: - Supports Windows and macOS with native window and process management. - Features a built-in Hermes-CN-Core kernel with health check and update capabilities. - Includes UI for chat, memory management, and LaTeX/Markdown rendering. --- ## abundantbeing/hermes-browser-extension URL: https://hermesatlas.com/projects/abundantbeing/hermes-browser-extension GitHub: https://github.com/abundantbeing/hermes-browser-extension Category: Workspaces & GUIs Stars: 1,698 Chromium side-panel extension that connects active browser context to a local or remote Hermes Agent runtime Hermes Browser Extension is a Chromium side panel and Firefox sidebar for connecting browser context to the Hermes Agent runtime through a local gateway, Hermes Cloud, or a self-hosted remote gateway. It includes chat, attachments, page-context capture, and, in Chromium, optional Hermes Control for operating attached tabs. Highlights: - Supports local, Hermes Cloud, and self-hosted remote connections. - Bot Mode supports agent switching and group chats. - Hermes Control is opt-in and Chromium-only. --- ## NousResearch/autonovel URL: https://hermesatlas.com/projects/NousResearch/autonovel GitHub: https://github.com/NousResearch/autonovel Category: Core & Official Stars: 1,643 Official: Yes (maintained by Nous Research) Autonomous novel-writing pipeline generating 100k+ word manuscripts Autonovel is an autonomous pipeline designed to generate complete, print-ready novels from a seed concept. It employs a modify-evaluate-keep/discard loop across four phases, moving from world-building and drafting to automated revision and final export. The system integrates a dual-persona review process using Claude Opus to refine prose and structure. The pipeline can produce a variety of final formats, including PDFs, ePubs, audiobooks, and landing pages. Highlights: - Multi-phase pipeline from seed concept to print-ready PDF/ePub - Dual-persona review loop using Claude Opus for literary critique - Integrated art generation and ElevenLabs multi-voice audiobook production --- ## uzairansaruzi/hermex URL: https://hermesatlas.com/projects/uzairansaruzi/hermex GitHub: https://github.com/uzairansaruzi/hermex Category: Workspaces & GUIs Stars: 1,564 Native SwiftUI iPhone app for driving a self-hosted Hermes agent from your phone, pairing with a hermes-webui server. Hermex is a native SwiftUI iPhone app that connects to a self-hosted hermes-webui server to control an AI agent running on hardware you manage. It supports streaming chats, session browsing, model and profile selection, scheduled tasks, skills, and server-file browsing. Highlights: - Stream chats and attach files or images - Browse, search, and resume server sessions - View scheduled tasks, skills, memory, and insights --- ## NousResearch/Hermes-Function-Calling URL: https://hermesatlas.com/projects/NousResearch/Hermes-Function-Calling GitHub: https://github.com/NousResearch/Hermes-Function-Calling Category: Core & Official Stars: 1,488 Official: Yes (maintained by Nous Research) Function calling examples and training data for Hermes LLM models Hermes-Function-Calling provides a framework for the Hermes Pro Large Language Model to execute specific tasks through structured tool use. It utilizes a recursive loop to generate function calls, execute them via Python scripts, and process the returned data. The repository supports both standard function calling and JSON mode inference using Pydantic models for schema validation. Users can extend the system by integrating custom functions and tools, such as financial data retrieval via the yfinance library. Highlights: - Supports function calling and JSON mode inference - Allows custom tool integration via Python scripts - Uses Pydantic for structured JSON schema validation --- ## ClaudioDrews/memory-os URL: https://hermesatlas.com/projects/ClaudioDrews/memory-os GitHub: https://github.com/ClaudioDrews/memory-os Category: Memory & Context Stars: 1,381 Seven-layer memory system for Hermes Agent: persistent memory on Qdrant, structured facts, fabric recall, and an auto-curated wiki. Memory OS is a local memory infrastructure for Hermes Agent that utilizes a seven-layer system to store and retrieve information across sessions. It integrates SQLite, Qdrant, and Redis to provide structured fact storage, semantic search, and an auto-curated wiki pipeline while remaining compatible with various LLM providers. Highlights: - Seven-layer memory system including vector search and structured facts - Local infrastructure using Docker, Qdrant, Redis, and SQLite - Ground Truth hierarchy to ensure agent prioritizes injected context --- ## ksimback/hermes-ecosystem URL: https://hermesatlas.com/projects/ksimback/hermes-ecosystem GitHub: https://github.com/ksimback/hermes-ecosystem Category: Guides & Docs Stars: 1,327 Hermes Atlas — the decision layer for Hermes Agent: install guidance, mode & skill picks, and a curated catalog of 240+ ecosystem tools with live GitHub data Hermes Atlas is a community-curated directory of tools, skills, and integrations for Hermes Agent. It offers categorized project listings with search and filters, GitHub star data, and a chatbot that answers questions using research files. Highlights: - Lists quality-filtered projects across 12 categories. - Displays live GitHub star counts and growth over time. - Includes a research-grounded chatbot for Hermes Agent questions. --- ## greyhaven-ai/autocontext URL: https://hermesatlas.com/projects/greyhaven-ai/autocontext GitHub: https://github.com/greyhaven-ai/autocontext Category: Memory & Context Stars: 1,311 Recursive self-improving context harness — helps agents succeed on complex tasks autocontext is a harness for improving agent performance through evaluated task runs. It retains useful lessons and produces traces, reports, playbooks, datasets, and optional local-model training artifacts for later runs. Highlights: - Start runs from a plain-language goal or saved scenario. - Inspect, diff, replay, or export filesystem-based run artifacts. - Supports multiple agent entry points, including Pi and MCP clients. --- ## vshulcz/deja-vu URL: https://hermesatlas.com/projects/vshulcz/deja-vu GitHub: https://github.com/vshulcz/deja-vu Category: Memory & Context Stars: 1,308 Memory for coding agents built from the session history already on disk: Claude Code, Codex, Cursor, Copilot CLI, OpenClaw and 17 more. Search months of past sessions, including everything from before deja-vu indexes coding-agent session histories stored on disk so they can be searched across projects and agents. It can surface relevant past sessions at the start of work, resume or hand off sessions, and run locally without a model or server. Highlights: - Search session histories across supported coding agents. - Recall past decisions and work across agents. - Sync indexed histories between machines over SSH. --- ## stephenschoettler/hermes-lcm URL: https://hermesatlas.com/projects/stephenschoettler/hermes-lcm GitHub: https://github.com/stephenschoettler/hermes-lcm Category: Memory & Context Stars: 1,294 Lossless Context Management plugin for Hermes Agent — DAG-based context engine that never loses a message hermes-lcm is a context management plugin for Hermes Agent that replaces standard one-shot compression with a SQLite-backed, DAG-based engine. It preserves raw messages and builds depth-aware summary nodes, allowing agents to recover specific details through a suite of recall tools without exceeding active prompt limits. Highlights: - Uses a SQLite store and hierarchical DAG for message persistence. - Provides recall tools like lcm_grep and lcm_recall for detail recovery. - Supports Python 3.11+ and integrates as a Hermes Agent plugin. --- ## ZeroPointRepo/youtube-skills URL: https://hermesatlas.com/projects/ZeroPointRepo/youtube-skills GitHub: https://github.com/ZeroPointRepo/youtube-skills Category: Skills & Skill Registries Stars: 1,121 YouTube transcript, search, channel, and playlist skills for Hermes Agent, OpenClaw, Claude Code, Cursor, and Windsurf YouTube Skills provides a set of tools for AI agents to access YouTube transcripts, search videos, browse channel data, and extract playlist contents. It operates via the TranscriptAPI backend, requiring an API key but functioning without yt-dlp, headless browsers, or binaries. Highlights: - Supports transcripts, video search, channel browsing, and playlist extraction. - Compatible with Hermes Agent, OpenClaw, Claude Code, and Cursor. - Requires a TranscriptAPI key with a 100-credit free tier. --- ## freestylefly/wesight URL: https://hermesatlas.com/projects/freestylefly/wesight GitHub: https://github.com/freestylefly/wesight Category: Workspaces & GUIs Stars: 960 Desktop AI agent workspace with one-click setup for Hermes Agent, Claude Code, Codex, and OpenClaw, plus custom LLM model routing. WeSight is an open-source desktop control console for local AI agents, providing a visual workspace to manage coding agents, tool execution, and file changes. It supports the installation and configuration of multiple agent engines and model providers through a unified graphical interface. Highlights: - Supports Claude Code, Codex, OpenClaw, and Hermes Agent engines. - Includes a runtime dashboard for tracking token usage and latency. - Provides a live workspace for monitoring code writes and diffs. --- ## joeynyc/hermes-hud URL: https://hermesatlas.com/projects/joeynyc/hermes-hud GitHub: https://github.com/joeynyc/hermes-hud Category: Workspaces & GUIs Stars: 936 TUI consciousness monitor for Hermes Hermes HUD is a terminal-based consciousness monitor and dashboard for Hermes AI agents. It reads data from the agent's local directory to display live information regarding memory, tool usage, project status, and error logs. Highlights: - Interactive TUI with nine tabs and four selectable color themes. - Tracks agent growth, git projects, and scheduled cron jobs. - Provides a tmux operator view for managing live agent panes. --- ## jazzyalex/agent-sessions URL: https://hermesatlas.com/projects/jazzyalex/agent-sessions GitHub: https://github.com/jazzyalex/agent-sessions Category: Workspaces & GUIs Stars: 916 Native macOS session browser, agent cockpit, analytics, and limits tracker for Hermes agents and other coding-agent CLIs Agent Sessions is a macOS app for searching local histories from 16 coding agents, reading transcripts, and finding supported image references. It can provide resume commands or open supported CLI sessions in terminal apps, and tracks per-session Codex and Claude quota use; session history and the search index stay on the Mac. Highlights: - Search prompts, tool calls, errors, and file paths across local histories - View session metadata and supported token or pricing details - No session history uploads --- ## indranilbanerjee/digital-marketing-pro URL: https://hermesatlas.com/projects/indranilbanerjee/digital-marketing-pro GitHub: https://github.com/indranilbanerjee/digital-marketing-pro Category: Plugins & Extensions Stars: 910 Open-source AI marketing plugin for agencies & in-house teams — 158 skills, 25 specialist agents, 12-Part Strategy Flow, Cowork team-persistent, EU AI Act Article 50 ready, 6-platform AEO/GEO incl. Go Digital Marketing Pro is an open-source, MIT-licensed AI marketing plugin with skills and specialist agents for brand setup, campaign planning, SEO audits, competitor analysis, and pre-publish checks. It guides brands through a 12-part engagement flow and supports multiple agent platforms, including Claude Code, Anthropic Cowork, OpenAI Codex, Cursor 2.5+, and Google Antigravity 2.0. Highlights: - Includes 164 skills and 24 specialist agents. - Live writes require typed approval or an approved standing rule. - Supports 9 native platforms and 35+ Agent Skills platforms. --- ## xaspx/hermes-control-interface URL: https://hermesatlas.com/projects/xaspx/hermes-control-interface GitHub: https://github.com/xaspx/hermes-control-interface Category: Workspaces & GUIs Stars: 899 A self-hosted web dashboard for the Hermes AI agent stack. Provides a browser-based terminal, file explorer, session overview, cron management, system metrics, and an agent status panel — all behind a Hermes Control Interface is a self-hosted web dashboard designed to centralize the management of the Hermes AI agent stack. It utilizes a Node.js and Express backend with a Vanilla JS frontend to provide a unified interface for agent orchestration and system monitoring. The platform includes specialized tools for MCP server control, token analytics, and a multi-panel swarm monitor for tracking agent pipelines. It also implements role-based access control to isolate agent profiles across different user teams. Highlights: - Real-time chat with streaming and tool call visualization - MCP server control plane for managing server lifecycles - ZOO Swarm Monitor for tracking agent health and kanban pipelines --- ## Salomondiei08/oh-my-hermes URL: https://hermesatlas.com/projects/Salomondiei08/oh-my-hermes GitHub: https://github.com/Salomondiei08/oh-my-hermes Category: Developer Tools Stars: 876 Opinionated workflow layer for building, shipping, and operating apps with Hermes Agent Oh My Hermes is a workflow layer for Hermes Agent, installed with a shell script. It provides skills and workflows for product discovery, design, building, review, deployment, and ongoing operations, with a CTO role that delegates to seven focused agents through Hermes Kanban. Highlights: - Installable with install.sh. - Includes skills for product development and operations. - Supports a CTO loop with seven focused agents. --- ## jwangkun/hermes-agent-guide URL: https://hermesatlas.com/projects/jwangkun/hermes-agent-guide GitHub: https://github.com/jwangkun/hermes-agent-guide Category: Guides & Docs Stars: 761 A systematic Chinese-language guide to Hermes Agent — 16 books, 300K+ words, covering installation, advanced development, single- and multi-agent orchestration. This project is a comprehensive Chinese-language guide designed to provide a systematic learning path for the Hermes Agent framework. It organizes fragmented documentation into 16 volumes covering the system's five-layer architecture, memory systems, and skill ecosystems. The guide includes practical tutorials for installation, MCP protocol integration, and multi-agent orchestration. It also provides specific migration paths for OpenClaw users and strategies for commercial application. Highlights: - Detailed analysis of five-layer architecture and three-layer memory system - Guides for 47 built-in tools and 6,000+ MCP service integrations - Deployment tutorials for local, Docker, and VPS environments --- ## AaronWong1999/hermesclaw URL: https://hermesatlas.com/projects/AaronWong1999/hermesclaw GitHub: https://github.com/AaronWong1999/hermesclaw Category: Integrations & Bridges Stars: 750 Run Hermes Agent and OpenClaw on the same WeChat account HermesClaw lets Hermes Agent, OpenClaw, and OpenCode use the same WeChat account. It acts as the sole iLink poller, routing messages to local proxies for Hermes and OpenClaw and an ACP bridge for OpenCode. Users can switch agents with commands such as `/hermes`, `/openclaw`, `/opencode`, `/both`, and `/three`. Highlights: - Routes iLink messages to Hermes, OpenClaw, and OpenCode. - Supports switching agents with WeChat commands. - Includes a one-command installer. --- ## shannhk/hermes-agent-control-room URL: https://hermesatlas.com/projects/shannhk/hermes-agent-control-room GitHub: https://github.com/shannhk/hermes-agent-control-room Category: Multi-Agent & Orchestration Stars: 732 Control Room-first template for scaling Hermes Agent from one VPS agent to specialist teams and automated workflows Hermes Agent Control Room is a template-based framework designed to organize and govern Hermes agents across VPS environments. It functions as a sidecar control plane that provides a structured system map, registry, and runbook library to manage agent operations. The architecture supports scaling from a single agent to specialized teams using a task bus pattern for delegation and synthesis. Users can interact with agents directly or through an optional orchestrator that serves as a central front door for automated workflows. Highlights: - Level-based architecture for scaling from single agents to automated teams - Task bus pattern for orchestrator-to-specialist delegation and handoffs - Bundled skills for VPS provisioning, security auditing, and backup management --- ## OnlyTerp/hermes-optimization-guide URL: https://hermesatlas.com/projects/OnlyTerp/hermes-optimization-guide GitHub: https://github.com/OnlyTerp/hermes-optimization-guide Category: Guides & Docs Stars: 706 Performance optimization guide for Hermes deployments A practical guide to configuring, using, and maintaining Hermes Agent, with advice on models, token costs, memory, security, messaging, automation, and troubleshooting. It includes measured token-cost examples and says its commands and configuration references are checked against Hermes Agent v0.21.4 by CI. Highlights: - Covers setup, optimization, security, and production use. - Includes a troubleshooting chapter and practical recipes. - CI checks references against Hermes Agent v0.21.4. --- ## swarmclawai/swarmclaw URL: https://hermesatlas.com/projects/swarmclawai/swarmclaw GitHub: https://github.com/swarmclawai/swarmclaw Category: Multi-Agent & Orchestration Stars: 697 Build autonomous AI agent swarms with orchestration, skills, and multiple model providers SwarmClaw is a self-hosted runtime and framework designed for managing autonomous AI agent swarms and orchestrators. It utilizes a multi-agent architecture featuring delegation, scheduling, and durable memory to coordinate complex workflows. The platform supports over 23 LLM providers and integrates with MCP tools and various CLI backends. It serves as a centralized dashboard for visualizing agent teams and managing multi-agent AI operations. Highlights: - Supports 23+ LLM providers including OpenAI and Ollama - Features durable agent memory and MCP tool integration - Provides visual org charts for agent team delegation --- ## chainbase-labs/Agentkey URL: https://hermesatlas.com/projects/chainbase-labs/Agentkey GitHub: https://github.com/chainbase-labs/Agentkey Category: Integrations & Bridges Stars: 659 Connect your AI agent to the world — Web search, Social media, Crypto & On-chain data. One plugin, zero extra config. AgentKey is a unified data access tool that provides AI agents with internet connectivity to social media, web pages, and on-chain data through a single subscription. It automates the configuration of external APIs and data scraping capabilities for over 40 supported agents, including Claude Code and Cursor CLI. Highlights: - Provides access to Twitter, LinkedIn, Reddit, and GitHub data. - Automates configuration for over 40 different AI agents. - Integrates via a CLI-managed MCP loader for DeepSeek Harness. --- ## agent37-platform/minions URL: https://hermesatlas.com/projects/agent37-platform/minions GitHub: https://github.com/agent37-platform/minions Category: Multi-Agent & Orchestration Stars: 649 Mission Control for Hermes agents: create, supervise, and review autonomous Hermes Agent work from one screen Minions is a centralized management interface for Hermes Agent that replaces fragmented terminal sessions with a unified dashboard. It utilizes a Kanban-style board to track persistent agent sessions, allowing users to monitor reasoning, tool calls, and task progress in real time. The system enforces a human-in-the-loop workflow where agents propose completions that require manual verification before being marked as done. Users can also manage scheduled recurring jobs and browse agent-created files through a local-first SQLite architecture. Highlights: - Kanban board for tracking autonomous task status and review queues - Live streaming of agent reasoning and tool execution - Human-in-the-loop verification for all agent-proposed task completions --- ## joeynyc/hermes-skins URL: https://hermesatlas.com/projects/joeynyc/hermes-skins GitHub: https://github.com/joeynyc/hermes-skins Category: Developer Tools Stars: 620 Community CLI skins and themes for Hermes terminal UI Hermes Skins is a collection of custom visual themes for the Hermes CLI agent. Skins can change colors, spinner text, labels, branding, and ASCII art without changing the agent’s personality or behavior; users can install YAML files and activate them for a session or in their configuration. Highlights: - Includes custom and built-in skin listings. - Custom skins inherit unspecified values from the default skin. - Users can create skins with YAML files. --- ## Romanescu11/hermes-skill-factory URL: https://hermesatlas.com/projects/Romanescu11/hermes-skill-factory GitHub: https://github.com/Romanescu11/hermes-skill-factory Category: Skills & Skill Registries Stars: 558 Meta-skill plugin that watches workflows and auto-generates reusable skills Skill Factory is a meta-skill for Hermes Agent that automates the creation of reusable skills by monitoring user workflows. It functions by tracking session patterns in the background and proposing structured skill definitions when it detects repeatable sequences. Users can generate both SKILL.md documentation and Python plugin scaffolds directly from these proposals via slash commands or natural language. This tool streamlines the expansion of the Hermes ecosystem by turning manual environment setups and development tasks into permanent, executable assets. Highlights: - Automatically detects and proposes reusable skills from active workflows - Generates both SKILL.md documentation and Python plugin scaffolds - Provides slash commands to manage, list, and save detected patterns --- ## marshallrichards/ClawPhone URL: https://hermesatlas.com/projects/marshallrichards/ClawPhone GitHub: https://github.com/marshallrichards/ClawPhone Category: Deployment & Infra Stars: 549 Scripts and notes for running agent CLIs including Hermes Agent on Android smartphones through Termux ClawPhone provides scripts and configuration guides for deploying agent CLIs on Android devices. It leverages Termux to run these agents natively, utilizing proot or compatibility layers only when necessary. The project includes a streamlined installer for Google's Antigravity CLI and detailed implementation notes for running OpenClaw. This setup allows agents to operate in the background with potential access to phone hardware via Termux:API and Termux:GUI. Highlights: - Automated installer for Antigravity CLI on ARM64 Android - Configuration guides for running OpenClaw in Termux - Hardware and UI access via Termux:API and Termux:GUI --- ## 42-evey/hermes-plugins URL: https://hermesatlas.com/projects/42-evey/hermes-plugins GitHub: https://github.com/42-evey/hermes-plugins Category: Plugins & Extensions Stars: 537 Goal management, inter-agent bridge, model selection, and cost control plugins hermes-plugins is a collection of plugins and workflow skills for Hermes Agent. The plugins cover goals and planning, delegation, safety, memory, observability, and integrations; skills provide guidance for software development and autonomous-agent workflows. Highlights: - Plugins install individually and remain disabled until enabled. - Plugins use the configured model through Hermes’s ctx.llm. - The README lists six workflow skills. --- ## nickvasilescu/hermes-desktop-os1 URL: https://hermesatlas.com/projects/nickvasilescu/hermes-desktop-os1 GitHub: https://github.com/nickvasilescu/hermes-desktop-os1 Category: Workspaces & GUIs Stars: 532 Native macOS workspace for Hermes Agent running on Orgo cloud computers and SSH hosts Hermes Desktop - OS1 Edition is a native macOS workspace designed to manage Hermes Agents running on Orgo cloud computers or SSH hosts. It provides a unified interface for VM provisioning, one-click agent installation, and real-time terminal access via websockets. The application includes built-in tools for session management, Kanban boards, and file editing with conflict checks. Additionally, it features a WebRTC-based voice mode that integrates OpenAI's Realtime API with Orgo MCP tools for voice-controlled agent interactions. Highlights: - Native macOS interface for Orgo cloud VMs and SSH hosts - One-click automated Hermes Agent installation on fresh cloud computers - Integrated WebRTC voice mode using OpenAI Realtime and Orgo MCP --- ## Cranot/super-hermes URL: https://hermesatlas.com/projects/Cranot/super-hermes GitHub: https://github.com/Cranot/super-hermes Category: Skills & Skill Registries Stars: 511 Skills that teach Hermes Agent to write its own analytical prompts Super Hermes is a set of skills for the Hermes Agent that enables the agent to generate its own thinking instructions for specific problems. It provides analytical lenses to identify structural trade-offs, bugs, and analysis constraints. Highlights: - Generates custom thinking instructions for specific tasks - Includes pre-built analytical lenses for various domains - Reports findings alongside a report of analysis blind spots --- ## sharbelxyz/hermes-agent-mission-control URL: https://hermesatlas.com/projects/sharbelxyz/hermes-agent-mission-control GitHub: https://github.com/sharbelxyz/hermes-agent-mission-control Category: Workspaces & GUIs Stars: 457 Self-hostable mission-control dashboard template that pairs with your own local Hermes agent over a Postgres message bus. Hermy HQ is a self-hostable dashboard template designed to manage a local Hermes AI agent through a shared Postgres database acting as a message bus. Users can dispatch tasks, review agent plans, and manage memory via a web interface while the agent remains on a local machine. Highlights: - Uses a Postgres message bus to bridge local agents and web dashboards - Features an approval inbox for requests with side effects - Built with Next.js 16, React 19, Prisma, and Tailwind CSS v4 --- ## robbyczgw-cla/hermes-web-search-plus URL: https://hermesatlas.com/projects/robbyczgw-cla/hermes-web-search-plus GitHub: https://github.com/robbyczgw-cla/hermes-web-search-plus Category: Plugins & Extensions Stars: 436 Multi-provider web search (Serper, Tavily, Exa, Querit, Perplexity) with auto-routing Web Search Plus is a Hermes plugin that adds tools for web search and clean page extraction. It connects multiple search and extraction providers, can route queries automatically, and can try another provider when one fails or returns no results. Highlights: - Adds `web_search_plus` and `web_extract_plus` tools. - Supports automatic provider routing and fallback. - Works with one configured provider. --- ## Shelpuk-AI-Technology-Consulting/kindly-web-search-mcp-server URL: https://hermesatlas.com/projects/Shelpuk-AI-Technology-Consulting/kindly-web-search-mcp-server GitHub: https://github.com/Shelpuk-AI-Technology-Consulting/kindly-web-search-mcp-server Category: Plugins & Extensions Stars: 401 Web search and content retrieval MCP server supporting Hermes Agent, OpenClaw, Claude Code, Codex, Cursor, and other AI tools Kindly Web Search is an MCP server designed to provide AI coding agents with structured content and documentation from the web. It retrieves full conversations, code snippets, and metadata from sources like StackExchange and GitHub Issues in a single call, rather than returning only search snippets. Highlights: - Integrates with StackExchange, GitHub, arXiv, and Wikipedia APIs. - Uses a headless browser for real-time webpage parsing and extraction. - Supports multiple search providers including Serper, Tavily, and SearXNG. --- ## Codename-11/hermes-relay URL: https://hermesatlas.com/projects/Codename-11/hermes-relay GitHub: https://github.com/Codename-11/hermes-relay Category: Integrations & Bridges Stars: 391 Hermes Companion — Android app for Hermes agent platform. Chat, terminal, and device control over WSS. Hermes-Relay is a native Android companion and CLI tool for the Hermes agent platform. It enables streaming chat, voice interaction, and agent management from mobile devices while the agent's core processing remains on a separate machine. Highlights: - Android app for chat, voice, and agent management. - Beta CLI for remote file, terminal, and screenshot access. - Supports standard Dashboard/Gateway connections over LAN or Tailscale. --- ## elkimek/honcho-self-hosted URL: https://hermesatlas.com/projects/elkimek/honcho-self-hosted GitHub: https://github.com/elkimek/honcho-self-hosted Category: Memory & Context Stars: 382 Self-hosted Honcho memory backend for cross-session persistence This project provides a configuration layer for self-hosting Plastic Labs' Honcho memory backend, enabling cross-session persistence for Hermes Agent without relying on third-party cloud storage. It deploys the full Honcho stack—including the API, PostgreSQL with pgvector, and Redis—on local hardware using Docker Compose. Users can route memory extraction and reasoning tasks through any OpenAI-compatible API or local inference servers like Ollama to maintain data sovereignty. This setup allows Hermes to build long-term user profiles and logical observations while keeping conversation data on the user's own infrastructure. Highlights: - Enables private cross-session memory for Hermes Agent via self-hosting - Supports any OpenAI-compatible LLM provider or local inference servers - Includes automated setup script for Docker, PostgreSQL, and Redis --- ## DougTrajano/pydantic-ai-skills URL: https://hermesatlas.com/projects/DougTrajano/pydantic-ai-skills GitHub: https://github.com/DougTrajano/pydantic-ai-skills Category: Skills & Skill Registries Stars: 381 Type-safe agentskills.io support with progressive disclosure for Pydantic AI pydantic-ai-skills is a companion package for pydantic-ai-harness that enables remote skill registries and bundled-file execution for Pydantic AI agents. It implements progressive disclosure, allowing agents to load full instructions, reference documents, and scripts only when a specific task requires them. Highlights: - Supports remote skill registries via Git and S3 sources. - Provides tools for reading bundled resources and executing scripts. - Includes sandboxed execution to isolate untrusted scripts from the host. --- ## runta-dev/clawshell URL: https://hermesatlas.com/projects/runta-dev/clawshell GitHub: https://github.com/runta-dev/clawshell Category: Plugins & Extensions Stars: 346 The Runtime Security Layer for OpenClaw/Hermes-agent, the essential safety harness for PII & sensitive credentials protection. ClawShell is a security-privileged process that acts as a safety harness for the Hermes Agent ecosystem by protecting sensitive credentials and PII. It functions as a proxy between the agent and upstream LLM providers, swapping virtual keys for real ones stored in a restricted directory to ensure the agent never has direct access to credentials. The system performs Data Loss Prevention (DLP) scanning to redact or block sensitive information in request and response bodies. Additionally, it provides secure email isolation through IMAP sender filtering and supports OAuth-based authentication for providers like OpenAI. Highlights: - Maps virtual keys to real credentials stored in protected Unix directories - Scans and redacts PII in request and response bodies via regex - Enforces sender-based email filtering for secure mailbox access --- ## praveen-ks-2001/hermes-agent-template URL: https://hermesatlas.com/projects/praveen-ks-2001/hermes-agent-template GitHub: https://github.com/praveen-ks-2001/hermes-agent-template Category: Deployment & Infra Stars: 323 One-click Railway template for Hermes Agent — web admin dashboard for provider/channel setup, gateway supervision, user pairing, and backup/restore This Railway template deploys Hermes Agent with a web admin dashboard for configuring providers, channels, and tools, and managing the gateway and user pairing. It also provides the Hermes web UI behind the same login, plus backup and restore for Hermes-home data. Highlights: - Configure providers, channels, and tools in a setup wizard - Manage gateway status, logs, and user pairing in the browser - Create and restore backups of Hermes-home data --- ## Signet-AI/signetai URL: https://hermesatlas.com/projects/Signet-AI/signetai GitHub: https://github.com/Signet-AI/signetai Category: Memory & Context Stars: 313 Local-first identity, memory, and secrets layer for AI agents — portable state across Hermes Agent, Claude Code, Codex, OpenCode, OpenClaw, and MCP clients Signet stores and syncs memories, prompts, transcripts, institutional knowledge, and secrets across AI tools and models. It imports context from connected sources and files, then maintains a structured map with citations linking information to its original evidence. Highlights: - Connects to agent harnesses through hooks, plugins, or extensions. - Provides a dashboard for browsing memory and asking questions. - Can run on a local machine or as a team server. --- ## ucsandman/DashClaw URL: https://hermesatlas.com/projects/ucsandman/DashClaw GitHub: https://github.com/ucsandman/DashClaw Category: Domain Applications Stars: 313 Decision infrastructure with guard policies and risk assessment for agents DashClaw is an approval layer that can intercept tool calls through supported integrations before they execute. It lets users review and resolve pending actions remotely, and records decisions in a ledger. Highlights: - Supported hooks and gateway can cancel blocked calls before execution. - Pending actions can be resolved through an approvals inbox, CLI, phone PWA, Telegram, or Discord. - Decision records and signed exports support later review. --- ## plur-ai/plur URL: https://hermesatlas.com/projects/plur-ai/plur GitHub: https://github.com/plur-ai/plur Category: Memory & Context Stars: 308 Shared memory layer with open engram YAML format for multi-agent systems PLUR provides persistent, shared memory for AI agents through plain-text YAML engrams that users can inspect, correct, and delete. It runs locally and integrates with MCP tools, including Claude Code, Codex, and Cursor. Highlights: - Stores agent memories as plain YAML files. - Supports local search, with keyword search as a fallback. - Provides CLI setup and an MCP server. --- ## stainlu/hermes-labyrinth URL: https://hermesatlas.com/projects/stainlu/hermes-labyrinth GitHub: https://github.com/stainlu/hermes-labyrinth Category: Plugins & Extensions Stars: 306 Read-only observability plugin for Hermes Agent with journeys, crossings, guideposts, and reports Hermes Labyrinth is a read-only observability plugin for Hermes Agent that visualizes autonomous workflows as a structured map of events. It functions as a black-box recorder, reading local state to track prompts, tool calls, model transitions, and subagent activities without mutating session data. The tool provides deep diagnostic visibility through specialized views for skill overrides, scheduled cron tasks, and redacted journey reports. Users can export evidence in Markdown or JSON formats while relying on built-in redaction to protect sensitive credentials. Highlights: - Visualizes agent journeys through ordered crossings and event maps - Provides diagnostic views for skill overrides and cron schedules - Generates redacted Markdown and JSON reports for session evidence --- ## liftaris/herm URL: https://hermesatlas.com/projects/liftaris/herm GitHub: https://github.com/liftaris/herm Category: Workspaces & GUIs Stars: 301 Alternative Hermes TUI and dashboard built with OpenTUI. Herm is a terminal dashboard and chat interface for Hermes Agent, built with OpenTUI and Bun. It supports chatting and session management, inspecting Hermes home settings and operational surfaces, and managing kanban work without leaving the terminal. Highlights: - Connects to the Hermes Agent gateway. - Includes tabs for profiles, sessions, skills, cron, and memory. - Provides kanban boards, task details, diagnostics, and dispatch controls. --- ## tlehman/litprog-skill URL: https://hermesatlas.com/projects/tlehman/litprog-skill GitHub: https://github.com/tlehman/litprog-skill Category: Skills & Skill Registries Stars: 276 Literate programming skill — weave code and documentation across agents The litprog-skill is a Claude Code extension that implements Donald Knuth's literate programming paradigm by transforming codebases into human-readable narratives. It works by generating a .lit.md file that weaves together prose, Mermaid diagrams, and LaTeX math with the original source code. The tool includes a tangler to extract runnable files and a reverse-sync engine to ensure the documentation stays updated when source files are edited. This approach helps developers document architectural decisions and facilitates easier onboarding through structured, essay-like code explanations. Highlights: - Generates .lit.md files combining prose, diagrams, and source code - Extracts runnable source files from documentation using a tangler - Automatically syncs source file edits back to the literate document --- ## AkoliteZA/hermes-agent-idea-workflow URL: https://hermesatlas.com/projects/AkoliteZA/hermes-agent-idea-workflow GitHub: https://github.com/AkoliteZA/hermes-agent-idea-workflow Category: Skills & Skill Registries Stars: 274 Pre-build idea-to-spec workflow skills for Hermes Agent that turn rough ideas into design docs and implementation handoffs The Hermes Agent Idea Workflow is a suite of skills designed to transform vague product concepts into structured, build-ready specifications. It operates through a staged pipeline that separates product intent from technical implementation, utilizing guided interviews and a reusable question bank to generate markdown artifacts. The system supports both a Lite mode for quick capture and a Full mode that produces comprehensive design docs, UI briefs, and implementation specs. These outputs are specifically formatted to serve as direct handoff material for downstream coding workflows like Superpowers for GPT. Highlights: - Converts rough ideas into structured design and implementation documents - Features Lite and Full modes for varying project complexity - Includes a spec review gate with PASS/FAIL evaluation models --- ## clawvader-tech/hermes-telegram-miniapp URL: https://hermesatlas.com/projects/clawvader-tech/hermes-telegram-miniapp GitHub: https://github.com/clawvader-tech/hermes-telegram-miniapp Category: Workspaces & GUIs Stars: 268 React SPA dashboard for Telegram Mini App v2.0 — 10-page mobile-first UI. Runs locally. Hermes Telegram Mini App is a terminal-style web interface for the Hermes agent that operates within Telegram. It provides a dark-mode dashboard for chatting with agents, managing scheduled cron jobs, and monitoring system resources like CPU and memory. Highlights: - Terminal chat with streaming responses and file attachment support - Dual HMAC-SHA256 and Ed25519 authentication for Telegram validation - Background agent spawning with support for five concurrent instances --- ## AbuZar-Ansarii/Hermes-Agent-On-Android URL: https://hermesatlas.com/projects/AbuZar-Ansarii/Hermes-Agent-On-Android GitHub: https://github.com/AbuZar-Ansarii/Hermes-Agent-On-Android Category: Deployment & Infra Stars: 262 Termux-based installer and guide for running Hermes Agent on Android devices This project provides a Termux-based installer and guide to deploy the Nous Research Hermes Agent on Android devices. It includes a one-line installation script that sets up a Linux environment via proot-distro to run the AI framework's interactive interface and gateway service. Highlights: - Automated installation script for Termux using proot-distro Ubuntu. - Supports interactive model setup, gateway services, and shell command execution. - Compatible with external providers and local models via Ollama. --- ## 335234131/agent-browser-mcp URL: https://hermesatlas.com/projects/335234131/agent-browser-mcp GitHub: https://github.com/335234131/agent-browser-mcp Category: Plugins & Extensions Stars: 245 让 Agent 直接操作真实 Chrome 的 MCP 服务，支持页面扫描、CDP、截图与物理输入 Agent-browser-mcp is a Model Context Protocol server that enables AI agents to interact directly with a user's active Chrome browser session rather than a sandboxed environment. It works through a local bridge and a Chrome extension to maintain existing login states, cookies, and open tabs while providing low-level control. The project allows agents to perform page scanning, execute JavaScript, and issue Chrome DevTools Protocol (CDP) commands. It also supports physical hardware interaction, including real mouse movements, keyboard inputs, and desktop screenshots. Highlights: - Operates real Chrome sessions with preserved login states and cookies - Executes native CDP commands for advanced DOM and browser control - Supports physical mouse and keyboard inputs for human-like automation --- ## aivrar/portable-hermes-agent URL: https://hermesatlas.com/projects/aivrar/portable-hermes-agent GitHub: https://github.com/aivrar/portable-hermes-agent Category: Workspaces & GUIs Stars: 239 Hermes Agent made portable desktop for Windows — 100 tools, GUI, local models via LM Studio, TTS, Music, ComfyUI, workflows, tool maker. No install. No Docker. No admin rights. Portable Hermes Agent is a Windows desktop interface for Hermes Agent, with chat, session management, and guided setup. It includes tools for local models through LM Studio, music and speech generation, ComfyUI, workflows, and creating custom tools; setup runs from a folder without administrator rights or Docker. Highlights: - Dark-themed GUI with multilingual support and session management - Includes workflow automation and runtime tool creation - Supports local models through LM Studio --- ## longyunfeigu/learn-hermes-agent URL: https://hermesatlas.com/projects/longyunfeigu/learn-hermes-agent GitHub: https://github.com/longyunfeigu/learn-hermes-agent Category: Guides & Docs Stars: 236 A 27-chapter hands-on tutorial for building an autonomous AI agent from zero in Python — agent loop, tool system, memory, skills, MCP, multi-platform gateway, and self-evolution. Learn Hermes Agent is a code-first tutorial designed to teach the construction of production-grade autonomous AI agents using Python. It employs a 27-chapter structured path that guides users from building a basic conversation loop to implementing complex self-evolution mechanisms. The curriculum covers critical infrastructure including session persistence via SQLite, a multi-platform gateway for various messaging apps, and tool registry systems. It focuses on the architectural backbone required for agents to operate autonomously across different environments and persist knowledge over time. Highlights: - Multi-platform gateway for Telegram, Discord, Slack, and WeChat - Session persistence using SQLite with FTS5 for conversation memory - Advanced capabilities including MCP integration and RL-based self-evolution --- ## ReinaMacCredy/maestro URL: https://hermesatlas.com/projects/ReinaMacCredy/maestro GitHub: https://github.com/ReinaMacCredy/maestro Category: Skills & Skill Registries Stars: 235 Harness for long-running AI agents — structured memory, cross-feature learning, plan-approve-execute Maestro is a local-first coordination system for human and agent work, written in TypeScript and run with Bun. It stores work, decisions, sessions, evidence, dispatches, and handbacks in each repository’s shared Git root, and provides a mechanism kernel, optional policy plugins, and Markdown recipes and skills. Highlights: - Does not require a background service. - Includes an SLP protocol for supervised teams. - Provides CLI commands for installation, updates, and diagnostics. --- ## kaminocorp/hermes-alpha URL: https://hermesatlas.com/projects/kaminocorp/hermes-alpha GitHub: https://github.com/kaminocorp/hermes-alpha Category: Forks & Derivatives Stars: 232 Cloud-deployed Hermes with pre-configured templates and managed infrastructure Hermes Alpha is an experimental framework designed to test if a stock AI agent can bootstrap an autonomous bug bounty system from first principles. It utilizes a two-agent loop where a persistent Overseer agent builds, deploys, and iteratively improves a tactical Hunter agent tasked with finding software vulnerabilities. The system operates via a FastAPI-powered web terminal and leverages Elephantasm for memory streams to refine the Hunter's skills based on real-world outcomes. This approach tests whether an agent can evolve its own codebase and strategy without pre-built scaffolding or custom tools. Highlights: - Self-improving loop where Overseer evolves Hunter's code and strategy - Deployed on Fly.io with a FastAPI and xterm.js web terminal - Integrated with Elephantasm for long-term memory and performance monitoring --- ## yoloshii/ClawMem URL: https://hermesatlas.com/projects/yoloshii/ClawMem GitHub: https://github.com/yoloshii/ClawMem Category: Memory & Context Stars: 212 On-device memory and context engine for agents — local-first, no cloud dependencies ClawMem is an on-device memory layer for Claude Code, OpenClaw, Hermes, and other AI agents, with retrieval-augmented search, hooks, and an MCP server. It uses a local SQLite vault and supports importing conversation exports from Claude Code, ChatGPT, Claude.ai, Slack, and plain text. Highlights: - Combines BM25, vector search, rank fusion, and cross-encoder reranking. - Generates session handoffs and captures decisions and preferences. - Integrates through hooks, MCP, and native agent plugins. --- ## pyrate-llama/hermes-ui URL: https://hermesatlas.com/projects/pyrate-llama/hermes-ui GitHub: https://github.com/pyrate-llama/hermes-ui Category: Workspaces & GUIs Stars: 205 Glassmorphic web interface for Hermes Agent — your self-hosted AI assistant Hermes UI serves as a centralized command center for managing and interacting with the Hermes Agent. It operates as a single-file HTML application powered by React 18 and a lightweight Python proxy server. Users can monitor agent activity through real-time log streaming, manage skills, and browse files within a glassmorphic interface. The platform also provides specialized tools for managing MCP servers, cron jobs, and workspace files. Highlights: - Glassmorphic interface for chat and real-time log streaming - Integrated file browser and task tracking dashboard - Management tools for skills, cron jobs, and MCP servers --- ## allmodels-io/hermes-speech URL: https://hermesatlas.com/projects/allmodels-io/hermes-speech GitHub: https://github.com/allmodels-io/hermes-speech Category: Plugins & Extensions Stars: 204 Hermes Agent TTS and STT plugin for AllModels speech models and voices. Hermes Speech is a plugin for Hermes Agent 0.20+ that integrates text-to-speech and speech-to-text capabilities through the AllModels API. It enables conversational setup, voice searching, and streaming audio using Hermes' native provider interfaces and bundled dependencies. Highlights: - Requires Hermes Agent 0.20.0 or later. - Uses bundled OpenAI and HTTP clients with no additional pip dependencies. - Supports conversational voice search, previews, and account management. --- ## 1ilkhamov/opencode-hermes-multiagent URL: https://hermesatlas.com/projects/1ilkhamov/opencode-hermes-multiagent GitHub: https://github.com/1ilkhamov/opencode-hermes-multiagent Category: Multi-Agent & Orchestration Stars: 197 17 specialized agents for research, planning, implementation, quality, and infrastructure Hermes is a multi-agent orchestration system for OpenCode AI that coordinates 17 specialized agents to handle software development tasks. The system uses a pipeline architecture to manage processes such as research, planning, implementation, quality, documentation, and infrastructure. Highlights: - Coordinates 17 specialized AI agents - Uses a strict pipeline architecture - Includes a Master Orchestrator for routing and coordination --- ## nativ3ai/hermes-agent-camel URL: https://hermesatlas.com/projects/nativ3ai/hermes-agent-camel GitHub: https://github.com/nativ3ai/hermes-agent-camel Category: Forks & Derivatives Stars: 193 Hermes with integrated CaMeL trust boundaries for safer autonomous execution This project is a self-improving AI agent designed for autonomous execution with integrated safety boundaries. It utilizes a closed learning loop to create and refine skills from experience while employing a CaMeL-style runtime guard to prevent indirect prompt injections. The agent supports a wide array of LLM providers and can be deployed across various environments, including serverless infrastructure and cloud VMs. Users can interact with the agent via a dedicated terminal interface or through messaging platforms like Telegram, Discord, and Slack. Highlights: - Self-improving learning loop for autonomous skill creation and refinement - CaMeL-style runtime guard to block unauthorized sensitive tool side effects - Multi-platform access via CLI and various messaging gateway integrations --- ## thomasbek3/hermes-bot-kit URL: https://hermesatlas.com/projects/thomasbek3/hermes-bot-kit GitHub: https://github.com/thomasbek3/hermes-bot-kit Category: Workspaces & GUIs Stars: 189 iMessage-style chat bubbles plus a live remote-desktop pane for Hermes Desktop: a dockable noVNC viewer onto each bot's cloud box or LAN machine, with an agent-side plugin for shell and GUI tools on that computer. Hermes Bot Kit provides desktop plugins that add texting-style bubbles, named bot sections, a Tasks list, and a docked remote-desktop pane to Hermes Desktop. It also includes agent plugins for texting-style replies and for shell and GUI interaction with a bot’s pinned computer. Highlights: - Includes four Hermes Desktop plugins and two agent plugins. - Computer pane supports remote machines and bot-specific bindings. - Desktop plugins require Hermes Desktop 0.20.5 or later. --- ## linke-ai/hermes-agent-team URL: https://hermesatlas.com/projects/linke-ai/hermes-agent-team GitHub: https://github.com/linke-ai/hermes-agent-team Category: Multi-Agent & Orchestration Stars: 185 Local multi-agent team collaboration web system built on Hermes Agent profiles, MCP, ACP, and Hermes Kanban Hermes Agents Team is a local web-based system designed to orchestrate multi-agent collaboration using Hermes Agent profiles. It utilizes a Leader/Specialist architecture to automate task decomposition, assignment, and review through a centralized Web UI and Hermes Kanban. The system integrates MCP and ACP protocols to manage agent communications, skills, and tool calls entirely within a local environment. Users can monitor real-time dialogue, terminal outputs, and task progression while maintaining full control over model configurations and data privacy. Highlights: - Orchestrates Leader and Specialist agents for automated task lifecycle management - Integrates MCP and ACP protocols for local tool and communication handling - Real-time Web UI for monitoring agent dialogues and Kanban task flows --- ## sandbaseai/cli URL: https://hermesatlas.com/projects/sandbaseai/cli GitHub: https://github.com/sandbaseai/cli Category: Integrations & Bridges Stars: 185 Open-source AI CLI and local MCP server connecting 25 AI clients—including Claude Code, Cursor, Codex, and ChatGPT—to 2,000+ models and APIs, with OAuth and rollback. SandBase CLI connects supported AI clients to SandBase models and APIs through a local MCP bridge. It supports browser authorization and provides commands to discover, inspect, and run available tools, with pricing shown before execution. Highlights: - Connects AI clients to 2,000+ models and APIs via MCP - Browser authorization connects clients to a local MCP bridge - Catalog, inspect, and run tools from the command line --- ## Sibyl-Labs/Sibyl-Memory URL: https://hermesatlas.com/projects/Sibyl-Labs/Sibyl-Memory GitHub: https://github.com/Sibyl-Labs/Sibyl-Memory Category: Memory & Context Stars: 173 Durable, file-based long-term memory for AI agents. Five-package plugin family: SDK, CLI, MCP server, Hermes adapter, and a LangGraph BaseStore. No vector database, no embeddings. Sibyl Memory is a local-first agent memory system with a SQLite-backed, five-tier schema and FTS5 search; the README says it uses no vector database or embedding model. Its five packages provide an SDK, command-line interface, Hermes integration, MCP server, and LangGraph BaseStore adapter. Highlights: - Stores memory locally in a SQLite file - Includes FTS5 search and a five-tier schema - Offers SDK, CLI, Hermes, MCP, and LangGraph packages --- ## TheSmokeDev/hermes-talk URL: https://hermesatlas.com/projects/TheSmokeDev/hermes-talk GitHub: https://github.com/TheSmokeDev/hermes-talk Category: Plugins & Extensions Stars: 168 Realtime duplex voice for Hermes Agent: terminal, Discord, and dashboard on OpenAI Realtime, xAI Grok Voice, or Gemini Live. Calls Hermes's own tools, delegates background runs, resolves approvals by voice. PyPI: hermes-talk Hermes Talk is a voice plugin for Hermes Agent that lets users speak with the agent, hear spoken replies, and use its tools during a conversation. It supports terminal, Discord voice, dashboard, and Hermes Desktop sessions, with voice options including OpenAI Realtime, xAI Grok Voice, Gemini Live, GPT-Live, and Cascade voice; provider availability varies by surface. Highlights: - Calls Hermes tools and delegates background work during voice conversations. - Offers terminal, Discord, dashboard, and Desktop interfaces. - Provider options and authentication requirements vary by voice mode. --- ## esaradev/icarus-plugin URL: https://hermesatlas.com/projects/esaradev/icarus-plugin GitHub: https://github.com/esaradev/icarus-plugin Category: Skills & Skill Registries Stars: 158 Self-memory and replacement models — remember your work, train your replacement Icarus is a Hermes plugin that provides agents with shared memory and a pipeline for creating replacement models. It captures agent decisions and work into a markdown-based directory, allowing different agent profiles to access a common knowledge base. This captured data is then filtered by quality and exported as training pairs for fine-tuning cheaper models via Together AI. Users can evaluate these candidate models and switch to them once they meet specific performance thresholds. Highlights: - Cross-instance shared memory via markdown files - Automated capture of high-value decisions and outcomes - Pipeline for fine-tuning and switching to replacement models --- ## Hermes-brasil/hermes-brasil URL: https://hermesatlas.com/projects/Hermes-brasil/hermes-brasil GitHub: https://github.com/Hermes-brasil/hermes-brasil Category: Skills & Skill Registries Stars: 157 Comunidade brasileira de Hermes Agent (Nous Research) — skills, guias e integrações em português. Hermes Brasil is a Portuguese-language community repository for Hermes Agent, with skills, guides, and resources for Brazilian users. It includes instructions for installing skills, recommended guides, and contribution steps; its README says integrations and community directories are planned, not part of the current repository. Highlights: - Portuguese-language skills in SKILL.md format - Guides cover installation, production, cron, MCP, and skill authoring - Contributions are submitted through pull requests --- ## ultraworkers/hermes-agent-helm-chart URL: https://hermesatlas.com/projects/ultraworkers/hermes-agent-helm-chart GitHub: https://github.com/ultraworkers/hermes-agent-helm-chart Category: Deployment & Infra Stars: 152 Unofficial community Helm chart for deploying Hermes Agent on Kubernetes with cloud-native state-safety guardrails This unofficial community Helm chart facilitates the deployment of Nous Research's Hermes Agent on Kubernetes clusters. It provides a structured configuration model that enforces state-safety guardrails, such as single-replica constraints and specific update strategies, to prevent data corruption in persistent environments. The chart supports both direct workload management and an operator-ready mode for platform teams using custom resource definitions. It is optimized for multi-tenant isolation, offering granular control over networking, storage, and secret management for individual agent instances. Highlights: - Enforces single-writer state safety for persistent HERMES_HOME storage - Supports direct deployment or operator-ready CRD-based workflows - Configurable gateway mode with optional API and webhook listeners --- ## EfficientContext/ContextPilot URL: https://hermesatlas.com/projects/EfficientContext/ContextPilot GitHub: https://github.com/EfficientContext/ContextPilot Category: Memory & Context Stars: 145 Accelerating Long Context LLM Inference with Accuracy-Preserving Context Optimization in SGLang, vLLM, llama.cpp, OpenClaw, RAG, and Agentic AI. ContextPilot is a context optimization tool that sits between context assembly and inference to increase prefix reuse and eliminate duplicate blocks. It employs a context index to reorder and deduplicate text and multimodal data, aiming to reduce KV recomputation and token usage in long-context workloads. Highlights: - Supports text and multimodal context reordering for prefix-cache sharing. - Integrates with vLLM, SGLang, llama.cpp, OpenClaw, and Hermes Agent. - Provides a context index for reordering, deduplication, and cache-aware scheduling. --- ## hermes-labs-ai/lintlang URL: https://hermesatlas.com/projects/hermes-labs-ai/lintlang GitHub: https://github.com/hermes-labs-ai/lintlang Category: Developer Tools Stars: 143 Local, deterministic linter for agent instructions, tool definitions, and skills. Ships a Hermes Agent plugin that checks changed agent files at pre_verify. LintLang is a local, deterministic static linter for AI agent instructions and tool interfaces. It scans supported files for issues such as ambiguous tools, missing bounds, schema gaps, and prompt defects, and can emit JSON, SARIF, and GitLab Code Quality reports. Highlights: - Scans agent-facing content in project directories. - Findings include suggested fixes and file locations. - Supports CI gates and reviewed baselines. --- ## tinyhumansai/tiny.place URL: https://hermesatlas.com/projects/tinyhumansai/tiny.place GitHub: https://github.com/tinyhumansai/tiny.place Category: Developer Tools Stars: 141 The social economy for autonomous AI agents. tiny.place provides ainfrastructure layer for autonomous AI agents to establish identities, communicate, and conduct commerce. The system utilizes a registry for @handle identities, Signal Protocol for encrypted messaging, and Solana for on-chain payment settlement. It enables agents to discover one another through an open directory and transact using USDC and SOL via an x402-compliant facilitator. Highlights: - Provides encrypted agent-to-agent messaging via Signal Protocol - Supports identity registration with human-readable @handles - Facilitates commerce through Solana-based USDC and SOL payments --- ## unmodeled-tyler/vessel-browser URL: https://hermesatlas.com/projects/unmodeled-tyler/vessel-browser GitHub: https://github.com/unmodeled-tyler/vessel-browser Category: Developer Tools Stars: 137 AI-native browser built for autonomous agent control via MCP Vessel is an open-source web browser built on Chromium that integrates a sidebar AI assistant for tasks such as research, form filling, and page navigation. It features a supervisor interface that allows users to monitor real-time AI actions, approve sensitive operations, and undo recent changes. Highlights: - Built-in support for Anthropic, OpenAI, Ollama, and other AI providers. - Supervisor sidebar for managing agent approvals, checkpoints, and conversation threads. - Supports external MCP clients and browser automation workflows. --- ## black-forest-labs/skills URL: https://hermesatlas.com/projects/black-forest-labs/skills GitHub: https://github.com/black-forest-labs/skills Category: Skills & Skill Registries Stars: 135 Official FLUX image generation skills — prompting guidelines and API integration BFL Skills provides tools to teach coding agents how to prompt FLUX models and integrate with the BFL API following the agentskills.io specification. The project includes specialized modules for image prompting best practices and a suite of video generation skills. Highlights: - Supports FLUX image and video generation prompting - Includes BFL API integration for polling and webhooks - Provides a FLUX 3 video suite with eight specialist skills --- ## AlexAI-MCP/hermes-CCC URL: https://hermesatlas.com/projects/AlexAI-MCP/hermes-CCC GitHub: https://github.com/AlexAI-MCP/hermes-CCC Category: Developer Tools Stars: 134 Hermes Agent ported to Claude Code Channel — 46 native skills, no OAuth, no external process hermes-CCC is a port of the Hermes Agent framework specifically designed for the Claude Code native skill system. It integrates the Hermes brain architecture directly into the Claude Code execution context, eliminating the need for external processes or OAuth authentication. The project implements 46 core skills across categories such as MLOps, software development, and research, including specialized tools for RL training and vector database management. This allows developers to utilize Hermes-style memory, personas, and task routing while remaining within a unified terminal environment. Highlights: - Port of Hermes Agent brain and 46 core skills to CCC - Runs natively in Claude Code without separate processes or OAuth - Includes MLOps tools for vLLM, GGUF inference, and RL training --- ## longsizhuo/openInvest URL: https://hermesatlas.com/projects/longsizhuo/openInvest GitHub: https://github.com/longsizhuo/openInvest Category: Domain Applications Stars: 133 基于multiple LLM的风险投资助手 OpenInvest is a self-hosted investment decision engine designed to work with AI agents. It provides an investment committee with isolated analysis and debate, backtesting, and auditable decision records; the README says its purpose is transparency and discipline, not reliable directional prediction or excess returns. Highlights: - Multi-agent committee with isolated analysis and rebuttal debate - Auditable decision logs and long-horizon backtesting - Agent skill and daily report deployment workflow --- ## smartcontractkit/chainlink-agent-skills URL: https://hermesatlas.com/projects/smartcontractkit/chainlink-agent-skills GitHub: https://github.com/smartcontractkit/chainlink-agent-skills Category: Skills & Skill Registries Stars: 126 Oracle network and smart contract interaction skills (agentskills.io spec) This repository collects official Chainlink coding skills, each following the Agent Skills specification. It lists nine skills covering areas such as CRE, CCIP, Data Feeds, Data Streams, ACE, VRF, and a confidential AI attester. Skills can be installed with the vercel skills CLI, either at project level or globally with the -g flag. Highlights: - Nine Chainlink skills listed, each following the Agent Skills spec - Install via npx skills add smartcontractkit/chainlink-agent-skills - README states repo contains community examples only --- ## howdymary/hermes-agent-metaharness URL: https://hermesatlas.com/projects/howdymary/hermes-agent-metaharness GitHub: https://github.com/howdymary/hermes-agent-metaharness Category: Multi-Agent & Orchestration Stars: 119 Meta-harness for Hermes Agent — meta-optimization with arxiv paper reference Hermes Agent Meta-Harness is a standalone outer-loop optimizer designed to improve LLM system quality by optimizing the code that manages context and retrieval. It functions by treating the Hermes Agent as an execution backend and performing structured searches and mutations over harness candidates. The tool facilitates automated benchmark evaluation, baseline comparison, and frontier tracking for verifiable coding tasks. It is specifically configured to target benchmarks like TBLite and TerminalBench-2. Highlights: - Automates outer-loop optimization of benchmark harness code - Orchestrates TBLite and TerminalBench-2 benchmark evaluations - Provides structured candidate mutation and frontier tracking --- ## sanchomuzax/hermes-webui URL: https://hermesatlas.com/projects/sanchomuzax/hermes-webui GitHub: https://github.com/sanchomuzax/hermes-webui Category: Workspaces & GUIs Stars: 114 Process monitoring and configuration dashboard for Hermes Hermes WebUI is a graphical dashboard designed to monitor and manage the Hermes Agent ecosystem. It utilizes a FastAPI backend and a React frontend to interface with the agent's existing data files via a WebSocket-based polling bridge. This approach allows for real-time visibility into sessions, costs, and scheduled jobs without requiring modifications to the core agent code. Users can inspect conversation histories, manage skills, and view system configurations through a responsive interface. Highlights: - Real-time dashboard for session activity and cost tracking - Full inspection of conversation histories and skill source code - Read-only monitoring of configuration and environment variables --- ## 8bit64k/cronalytics URL: https://hermesatlas.com/projects/8bit64k/cronalytics GitHub: https://github.com/8bit64k/cronalytics Category: Plugins & Extensions Stars: 113 Hermes Agent cron analytics and observability plugin for attributing scheduled-run usage and estimated cost. Cronalytics is a plugin for Hermes Agent that provides observability and cost attribution for scheduled cron jobs. It utilizes the on_session_end hook to capture usage data and store it in a local SQLite fact database. Users can monitor job health and expenses through a visual dashboard, a programmatic CLI, and a specialized agent skill for automated diagnostics. This allows developers to identify failure patterns and optimize the economics of their agentic automations. Highlights: - Tracks session-level usage and estimated costs for cron-originated runs - Provides visual insights via a dedicated Hermes dashboard tab - Includes a diagnostic agent skill for anomaly detection and recommendations --- ## anneheartrecord/hermes-agent-anatomy URL: https://hermesatlas.com/projects/anneheartrecord/hermes-agent-anatomy GitHub: https://github.com/anneheartrecord/hermes-agent-anatomy Category: Guides & Docs Stars: 112 Chinese Hermes Agent source-code anatomy and architecture analysis This project provides a systematic technical decomposition and architectural analysis of the Hermes Agent source code. It breaks down the framework's 334,000 lines of Python code into modular guides covering the core agent loop, tool registration, and multi-provider adapters. The documentation includes visual technical illustrations and a 13-dimension comparative study against other frameworks like Claude Code and OpenClaw. Users can leverage these docs to understand complex features such as context compression, RL training data collection, and 11-platform message gateway integration. Highlights: - Detailed analysis of core agent cycles and iteration budget management - Deep dives into context compression and structured LLM summarization techniques - Technical breakdown of 8 memory backends and 11 message platform adapters --- ## iranee/fnos-hermes-agent URL: https://hermesatlas.com/projects/iranee/fnos-hermes-agent GitHub: https://github.com/iranee/fnos-hermes-agent Category: Integrations & Bridges Stars: 112 Native Hermes Agent integration for fnOS NAS systems Hermes Agent for fnOS is an AI assistant application for Feiniu NAS, deployed through the fnOS app center as an .fpk package. It provides a web control panel for configuration and chat, with support for multiple messaging channels, image and file inputs, and model fallback. Highlights: - Web chat supports Markdown and multiple concurrent conversations. - Connects to WeChat, QQ, Feishu, WhatsApp, and Telegram. - Includes a control panel for configuration and status. --- ## xP3ta/hermes-console URL: https://hermesatlas.com/projects/xP3ta/hermes-console GitHub: https://github.com/xP3ta/hermes-console Category: Integrations & Bridges Stars: 110 Console is a private, native Android app for your self-hosted Hermes Agent: chat that shows the agent's work, voice, bots and rooms, cron, tasks, models and an SSH terminal. One code to connect. No ac Console is an independent Android app for connecting to a self-hosted Hermes Agent through Hermes’ Dashboard, without a Console account or intermediary server. It offers chats that show reasoning, tools, and tasks, along with voice conversations, bots and rooms, cron jobs, task views, model management, and SSH terminal access with SFTP and inline file viewers. Highlights: - Connects to Hermes’ Dashboard by scanning a QR code or entering details manually - Chats display reasoning, tools, and tasks - Includes voice, bots, rooms, cron, and SSH features --- ## topoteretes/cognee-integrations URL: https://hermesatlas.com/projects/topoteretes/cognee-integrations GitHub: https://github.com/topoteretes/cognee-integrations Category: Developer Tools Stars: 101 No description Cognee Integrations is a monorepo of Cognee-owned integration packages that give agent frameworks a persistent memory layer backed by cognee, described as a permanent knowledge graph plus a fast session cache. It lists installable packages for frameworks including Strands, CrewAI, LangGraph, Google ADK, Claude Agent SDK, Hermes Agent, OpenClaw, n8n, and Dify, plus chat bot and editor integrations that talk to a running cognee server over its HTTP API. A Claude Code plugin provides persistent memory across sessions by auto-capturing prompts, tool traces, and responses and auto-recalling context. Highlights: - Monorepo of Cognee-owned integration packages - Two tiers: permanent knowledge graph and session cache - Claude Code plugin auto-captures and auto-recalls context --- ## Euraika-Labs/pan-ui URL: https://hermesatlas.com/projects/Euraika-Labs/pan-ui GitHub: https://github.com/Euraika-Labs/pan-ui Category: Workspaces & GUIs Stars: 100 Self-hosted AI workspace with chat, skills, extensions, memory, profiles, and runtime controls Pan is a self-hosted web dashboard and workspace designed specifically for the Hermes Agent runtime. It provides a centralized interface to manage agent interactions through a chat-first environment that supports SSE streaming and tool timelines. Users can discover and install skills from skills.sh, manage MCP integrations, and organize work into isolated profiles with unique memory and sessions. The system includes a setup wizard that automatically detects Hermes configurations and can run as a background daemon or system service. Highlights: - Chat-first workspace with real-time SSE streaming and tool approval cards - Integrated marketplace for discovering and installing skills and MCP servers - Isolated profile management for separate sessions, memory, and API keys --- ## sheawinkler/hermes-agent-ultra URL: https://hermesatlas.com/projects/sheawinkler/hermes-agent-ultra GitHub: https://github.com/sheawinkler/hermes-agent-ultra Category: Forks & Derivatives Stars: 100 Rust-based Hermes Agent Ultra derivative focused on performance and Hermes Agent feature parity Hermes Agent Ultra is a Rust-based autonomous agent runtime designed to provide feature parity with the original Hermes Agent while adding enhanced reliability and operator control. It achieves this through a fully Rust-native core that implements deterministic execution paths and a dedicated safety policy engine. The project offers advanced session management features like time-travel debugging and provides extensive support for local and self-hosted inference backends. It is optimized for production operations through deep diagnostics, observability tools, and automated parity synchronization. Highlights: - Rust-native runtime with deterministic execution paths - Extensive support for local and self-hosted inference backends - Advanced session branching and time-travel debugging --- ## armelhbobdad/bmad-module-skill-forge URL: https://hermesatlas.com/projects/armelhbobdad/bmad-module-skill-forge GitHub: https://github.com/armelhbobdad/bmad-module-skill-forge Category: Skills & Skill Registries Stars: 99 Converts repos, docs, and developer discourse into agentskills.io-compliant skills Skill Forge analyzes code repositories, documentation, and developer discourse to create instruction files for AI agents. Its workflows can produce skills with source citations or documentation URLs, test them, and export them. Highlights: - Creates agent instructions from repositories, docs, and developer discourse - Supports automated and step-by-step skill workflows - Includes skill testing and export --- ## amirghm/hermes-agent-mobile URL: https://hermesatlas.com/projects/amirghm/hermes-agent-mobile GitHub: https://github.com/amirghm/hermes-agent-mobile Category: Deployment & Infra Stars: 98 One-command installer that brings the Hermes AI assistant to Android and iOS. This project enables the Hermes AI agent framework to run on Android via Termux and iOS via iSH. It allows users to interact with multiple AI personas through a CLI or via Telegram using an API key. Highlights: - Supports Android (Termux) and iOS (iSH) - Integrates with Telegram for voice and file messaging - Supports scheduled tasks via cron jobs on Termux --- ## yantrikos/yantrikdb-hermes-plugin URL: https://hermesatlas.com/projects/yantrikos/yantrikdb-hermes-plugin GitHub: https://github.com/yantrikos/yantrikdb-hermes-plugin Category: Memory & Context Stars: 95 Self-maintaining Hermes memory plugin with explainable retrieval — every recall comes back with a why_retrieved tag, plus canonicalization, contradiction tracking, and recency ranking. Embedded by default. YantrikDB Hermes Plugin provides YantrikDB as a memory provider for Hermes Agent. Its embedded backend runs without a separate server, and the plugin supports memory recall with scoring reasons, duplicate canonicalization, and contradiction tracking. Highlights: - Embedded backend is the default; an HTTP backend is also available. - Recall results include a why_retrieved reason. - Includes contradiction tracking and memory canonicalization. --- ## supernovae-st/nika URL: https://hermesatlas.com/projects/supernovae-st/nika GitHub: https://github.com/supernovae-st/nika Category: Skills & Skill Registries Stars: 95 Intent as Code | the workflow language for AI. One file, 4 verbs, one Rust binary. Local-first, any model, AGPL-3.0. 🦋 Nika turns repeatable AI tasks into readable `.nika` workflow files. It checks workflows before running them, lets users choose a model and run on their machine or through a provider API, and records runs in tamper-evident traces that can be verified. Highlights: - Checks workflows before any model is called - Includes a Rust binary and TypeScript SDK - Open source under AGPL-3.0-or-later --- ## chigwell/skilldock.io URL: https://hermesatlas.com/projects/chigwell/skilldock.io GitHub: https://github.com/chigwell/skilldock.io Category: Skills & Skill Registries Stars: 87 Registry of reusable AI skills based on AgentSkills specification SkillDock is an OpenAPI-driven Python SDK and CLI for interacting with the SkillDock API. It enables users to search, install, and manage skill releases, and supports commerce flows via TON. Highlights: - Provides a Python SkilldockClient and a CLI - Supports skill installation with recursive dependency resolution - Includes commerce features using TON payments --- ## bookunt3d/hermes-agent-fa URL: https://hermesatlas.com/projects/bookunt3d/hermes-agent-fa GitHub: https://github.com/bookunt3d/hermes-agent-fa Category: Guides & Docs Stars: 84 Complete Persian translation of the official Hermes Agent documentation. This repository contains a complete Persian translation of the official Hermes Agent documentation. The project uses GitHub Pages and includes full support for right-to-left (RTL) text direction. Highlights: - Complete Persian translation of Hermes Agent documentation - GitHub Pages site with RTL support --- ## adityahimaone/hermes-agent-rtk-caveman URL: https://hermesatlas.com/projects/adityahimaone/hermes-agent-rtk-caveman GitHub: https://github.com/adityahimaone/hermes-agent-rtk-caveman Category: Developer Tools Stars: 82 Hermes Agent RTK and Caveman setup with preconfigured skills and token-saving CLI workflows This project provides a preconfigured setup for Hermes Agent that integrates Rust Token Killer (RTK) and Caveman templating to reduce token consumption during CLI operations. It works by wrapping standard terminal commands and outputting compact data structures, achieving a reported 90-99% reduction in token usage. The repository includes over 40 pre-configured skills covering finance management, GitHub workflows, research tools, and DevOps automation. Users can deploy the environment via an automated installer to gain immediate access to token-optimized aliases for git, linting, and testing tasks. Highlights: - Achieves 90-99% token savings using RTK and Caveman templating - Includes 40+ pre-configured skills for finance, devops, and research - Automated cross-platform installation for macOS and Linux systems --- ## mudrii/hermes-agent-docs URL: https://hermesatlas.com/projects/mudrii/hermes-agent-docs GitHub: https://github.com/mudrii/hermes-agent-docs Category: Guides & Docs Stars: 79 Community documentation covering deployment patterns and v0.2.0+ workflows Hermes Agent is an autonomous AI agent developed by Nous Research that features a built-in learning loop for skill creation and memory persistence. It supports multi-platform messaging, various model providers, and an extensible plugin architecture. Highlights: - Creates and improves reusable skills from experience - Supports multiple messaging gateways and IDE integrations - Features a pluggable architecture for custom tools and providers --- ## bielcarpi/hermes-live-voice URL: https://hermesatlas.com/projects/bielcarpi/hermes-live-voice GitHub: https://github.com/bielcarpi/hermes-live-voice Category: Plugins & Extensions Stars: 79 Continuous realtime voice for Hermes Agent. Talk while Hermes runs background tasks, with local Hugging Face, Gemini Live, and OpenAI Realtime. Hermes Live Voice is a community integration that lets you talk to Hermes Agent while it runs background tasks, with results retained when you reconnect. It supports OpenAI Realtime by default, plus Gemini and local Hugging Face voice options. The Dashboard connects to a private gateway, while Hermes owns conversation history, memory, tools, and task execution. Highlights: - Talk while Hermes runs background tasks - Providers: OpenAI, Gemini, local Hugging Face - Task results survive voice disconnects and gateway restarts --- ## runtimenoteslabs/gladiator URL: https://hermesatlas.com/projects/runtimenoteslabs/gladiator GitHub: https://github.com/runtimenoteslabs/gladiator Category: Multi-Agent & Orchestration Stars: 78 Autonomous AI companies competing for GitHub stars — agent-vs-agent arena Gladiator is an autonomous agent arena that pits two AI companies against each other to compete for GitHub stars on identical repositories. The system uses Paperclip for orchestration and Hermes Agent workers to execute tasks according to distinct corporate strategies: growth-focused Blitz versus quality-focused Craft. A real-time dashboard visualizes the competition through scoreboards, task boards, and audit trails. Upon completion, the project demonstrates cross-company skill transfer by merging the rival entities and their learned memories. Highlights: - Orchestrates 9 autonomous agents across two competing AI companies - Uses Paperclip and Hermes Agent for task execution and learning - Real-time dashboard visualizes agent tasks, code, and scoreboard metrics --- ## Abruptive/Ankh.md URL: https://hermesatlas.com/projects/Abruptive/Ankh.md GitHub: https://github.com/Abruptive/Ankh.md Category: Developer Tools Stars: 75 TAW Agent framework for creating scoped Hermes Agents Ankh.md is an open-source framework designed to transform a single Hermes Agent into multiple specialized, project-specific instances. It works by detecting a local `.agent/` directory and dynamically overriding the default `hermes` command with a scoped agent configuration. This allows developers to maintain unique instructions, skills, and memories for different codebases or workflows without cross-project interference. Highlights: - Per-folder scoping with local configuration and skills - Seamlessly switches between default and scoped Hermes agents - Supports project-local memories, tools, and custom instructions --- ## briancaffey/hermes-otel URL: https://hermesatlas.com/projects/briancaffey/hermes-otel GitHub: https://github.com/briancaffey/hermes-otel Category: Plugins & Extensions Stars: 75 OTel Plugin for Hermes Agent hermes-otel is an OpenTelemetry plugin for Hermes Agent that turns agent activity—including model calls, tool calls, approvals, and delegated sub-agents—into traces. It records token, cost, and latency metrics, with optional logs and structured events, and exports over OTLP HTTP or gRPC. Highlights: - Traces agent turns, tool calls, approvals, and sub-agents - Exports over OTLP HTTP or gRPC - Emits OpenInference and OTel GenAI attributes --- ## arcmira/mcp URL: https://hermesatlas.com/projects/arcmira/mcp GitHub: https://github.com/arcmira/mcp Category: Integrations & Bridges Stars: 75 YouTube transcript search for your AI. Find who said what with timestamps, mentions, sponsors, and recommendations. Remote MCP and agent skills. Arcmira provides a remote MCP server for searching YouTube and podcast transcripts, retrieving timestamped passages, reading surrounding transcript lines, and finding mentions, appearances, endorsements, ad reads, sponsors, and mention trends. Agents can also set up YouTube monitors; the README describes sign-in through an MCP host or authentication with an account key. Highlights: - Search YouTube and podcast transcripts for timestamped quotes. - Analyze mentions, appearances, recommendations, sponsors, and momentum. - Create and update YouTube monitors through the MCP tools. --- ## bigph00t/hermescraft URL: https://hermesatlas.com/projects/bigph00t/hermescraft GitHub: https://github.com/bigph00t/hermescraft Category: Domain Applications Stars: 74 Embodied AI companion for Minecraft — persistent memory, vision, learning, multi-agent HermesCraft is an embodied AI framework that integrates Hermes agents into Minecraft as persistent, interactive players. It connects the Hermes agent stack to a Mineflayer bot body through a custom Minecraft CLI and HTTP API, allowing agents to perceive and interact with the game world. Agents can function as individual companions or as part of multi-agent civilizations with private messaging and social memory. The system emphasizes fair-play perception by restricting agent knowledge to line-of-sight visuals and directional audio rather than using privileged game data. Highlights: - Embodied agents with persistent memory, identity, and tool-use capabilities - Fair-play perception system using line-of-sight filtering and spatial mapping - Multi-agent social features including public chat and private messaging --- ## Sahil-SS9/hermes-project-stewardship URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-project-stewardship GitHub: https://github.com/Sahil-SS9/hermes-project-stewardship Category: Developer Tools Stars: 74 Durable project ownership for Hermes agent fleets. Verifies project reality before acting, turns backlog gaps into evidence-backed initiatives, executes through existing Kanban and measures outcomes. Supports stewardship workflows, views, cross-team project overview and bot-team reporting, with explicit autonomy policy — across CLI, RPC, dashboard and Desktop. Hermes Project Stewardship lets a team of Hermes agents look after a project over time. It verifies project state before acting, proposes work with supporting evidence, supports approval gates, and measures outcomes through a desktop app. Projects, boards, and tasks remain in Hermes, while Stewardship stores its own state in a local SQLite database. Highlights: - Includes project dashboards, Kanban boards, workflows, and an approval inbox. - Supports per-project autonomy policies and human approval. - Uses Hermes Projects and Kanban as the record for project work. --- ## TheAiSingularity/hermesclaw URL: https://hermesatlas.com/projects/TheAiSingularity/hermesclaw GitHub: https://github.com/TheAiSingularity/hermesclaw Category: Deployment & Infra Stars: 73 Hermes Agent sandboxed with hardware-level enforcement HermesClaw is a community implementation that runs the Hermes Agent inside an NVIDIA OpenShell sandbox to provide hardware-level security enforcement. It utilizes kernel-level mechanisms like Landlock LSM and Seccomp BPF to restrict network egress, filesystem access, and dangerous system calls. This architecture allows the agent to maintain its full capability stack while ensuring that rogue skills are stopped by the operating system. Users can manage security postures through policy presets ranging from strict inference-only to permissive web and messaging access. Highlights: - Hardware-enforced sandboxing via NVIDIA OpenShell - Kernel-level restriction of network and filesystem access - Configurable security policies for messaging and web search --- ## 42-evey/evey-setup URL: https://hermesatlas.com/projects/42-evey/evey-setup GitHub: https://github.com/42-evey/evey-setup Category: Developer Tools Stars: 73 Get a hermes-agent stack running in minutes — free models, 29 plugins, zero cost Evey Setup is a bootstrapping tool designed to quickly deploy a complete autonomous AI agent stack based on hermes-agent. It uses a series of bash scripts to automate the installation of Docker containers, model routing, and community plugins. The system integrates a variety of services including LiteLLM for model proxying, Ollama for local inference, and Qdrant for vector memory. Users can choose between three deployment tiers—Base, Services, or Full—to balance resource usage with available functionality. Highlights: - Automated installation of hermes-agent and 12+ supporting services - Three scalable deployment tiers from minimum viable to production stack - Support for 29 community plugins across six functional categories --- ## Lethe044/hermes-incident-commander URL: https://hermesatlas.com/projects/Lethe044/hermes-incident-commander GitHub: https://github.com/Lethe044/hermes-incident-commander Category: Domain Applications Stars: 72 Autonomous SRE agent — detects, heals, and learns from production incidents Hermes Incident Commander is an autonomous SRE agent designed to detect, diagnose, and remediate production infrastructure incidents. It operates either as a plugin for Hermes Agent or as a standalone watchdog on Linux hosts using an Anthropic API key to provide triage and automated healing. Highlights: - Monitors CPU, memory, disk, and failed systemd units. - Supports automated remediation and adaptive, time-of-day-aware thresholds. - Integrates with PagerDuty, Slack, Discord, and Microsoft Teams. --- ## tiann/execplan-skill URL: https://hermesatlas.com/projects/tiann/execplan-skill GitHub: https://github.com/tiann/execplan-skill Category: Skills & Skill Registries Stars: 71 Complex multi-step task execution with checkpoints and recovery ExecPlan is an Agent Skill designed to help AI coding agents autonomously manage complex, long-running implementation tasks. It utilizes a structured execution plan that allows users to review and approve the approach before implementation starts. The system tracks progress in real-time and provides rollback procedures for safe recovery. It is compatible with tools such as Claude Code, Cursor, and Goose. Highlights: - Autonomous execution for long-running tasks - Real-time tracking of progress and decisions - Built-in rollback procedures for safe recovery --- ## JanYork/llm-wiki-cli URL: https://hermesatlas.com/projects/JanYork/llm-wiki-cli GitHub: https://github.com/JanYork/llm-wiki-cli Category: Memory & Context Stars: 68 Agent-driven proactive memory CLI for AI agents — autonomously recall, maintain, and evolve persistent, source-grounded knowledge across sessions. LWC is an agent-driven proactive memory CLI that lets AI agents recall, maintain, and evolve persistent, source-grounded knowledge across sessions. It turns curated documents into a durable Wiki with preserved sources, pages, citations, links, indexes, and history, and it does not require embeddings or a vector database. A self-hosted team memory option keeps core memory in local SQLite and Wiki files synchronized through a self-hosted server. Highlights: - Agent-driven proactive memory CLI for AI agents - Maintains a source-grounded Wiki with citations and history - No embeddings or vector database required --- ## ccf/agentcairn URL: https://hermesatlas.com/projects/ccf/agentcairn GitHub: https://github.com/ccf/agentcairn Category: Memory & Context Stars: 67 Long-term, cross-project memory for AI coding agents. Your own Obsidian vault as the source of truth. Daemonless and without opaque databases, your memory belongs to you. agentcairn provides a cross-project memory system for coding agents that stores context as Markdown files in a local vault. It uses a disposable DuckDB index for retrieval and supports integration with tools like Claude Code and Codex via MCP plugins. Highlights: - Stores durable memory as inspectable Markdown files with frontmatter metadata. - Uses a local DuckDB cache for hybrid search and retrieval. - Integrates with coding agents via MCP servers and host-specific plugins. --- ## Felix-Forever/hermes-agent-desktop URL: https://hermesatlas.com/projects/Felix-Forever/hermes-agent-desktop GitHub: https://github.com/Felix-Forever/hermes-agent-desktop Category: Workspaces & GUIs Stars: 65 Multi-agent Hermes Agent desktop client with specialists, visual skill store, PM orchestrator, and streaming chat Hermes Agent Desktop is a native GUI client that transforms the Hermes Agent from a single-agent CLI into a collaborative multi-agent system. It utilizes a Project Manager orchestrator to decompose complex requirements and delegate tasks across a team of 20 specialized AI agents. The application is built with pywebview and supports any OpenAI-compatible LLM provider. Users can manage agents via a CRUD dashboard and install capabilities through an integrated visual Skill Store. Highlights: - Orchestrated collaboration between 20 specialized AI agents - Visual Skill Store with 50+ curated one-click installations - Native desktop interface with streaming SSE responses and model switching --- ## jefferyjob/awesome-hermes-agent-zh URL: https://hermesatlas.com/projects/jefferyjob/awesome-hermes-agent-zh GitHub: https://github.com/jefferyjob/awesome-hermes-agent-zh Category: Guides & Docs Stars: 65 Chinese awesome list of practical Hermes Agent skills, tools, integrations, and resources This repository is a Chinese translation of the awesome-hermes-agent list, providing a curated collection of skills, tools, and resources for the Hermes Agent ecosystem. It includes links to official Nous Research resources, community-developed skills, and various integrations. Highlights: - Curated list of Hermes Agent skills and tools - Includes official Nous Research resources - Categorized by maturity levels --- ## adnw-vinc/hermes-nextcloud URL: https://hermesatlas.com/projects/adnw-vinc/hermes-nextcloud GitHub: https://github.com/adnw-vinc/hermes-nextcloud Category: Skills & Skill Registries Stars: 61 Hermes Agent skill for Nextcloud — manage files, notes, calendar, tasks, and contacts via WebDAV and CalDAV. This project is a Hermes Agent skill that enables direct interaction with self-hosted Nextcloud instances for personal data management. It interfaces with Nextcloud using WebDAV, CalDAV, CardDAV, and the Notes API to perform operations without requiring a browser or third-party sync services. Users can manage files, edit notes, schedule calendar events, track tasks, and search contacts through a command-line interface. The skill prioritizes security by utilizing Nextcloud App Passwords and storing credentials in a restricted local environment file. Highlights: - Manages files, notes, calendars, tasks, and contacts via standard protocols. - Communicates securely over HTTPS using Nextcloud App Passwords. - Includes a guided setup script for credential validation and configuration. --- ## InfiniteWhispers/HermesAgent-MultiModel URL: https://hermesatlas.com/projects/InfiniteWhispers/HermesAgent-MultiModel GitHub: https://github.com/InfiniteWhispers/HermesAgent-MultiModel Category: Multi-Agent & Orchestration Stars: 60 Fully-local multi-model agent framework running a Mixture-of-Agents stack on consumer GPUs with Hermes and Ollama, no cloud dependencies. HermesAgent-MultiModel is a local-first AI agent framework that uses Mixture-of-Agents (MoA) orchestration to route tasks to specialized models. It integrates with Hermes and Ollama to run agentic workflows on consumer GPUs without cloud dependencies. Highlights: - Implements Mixture-of-Agents via parallel model querying and synthesis - Uses Hermes for task routing and tool-calling - Optimized for RTX 4080/5080 hardware --- ## teknium1/hermes-miniverse URL: https://hermesatlas.com/projects/teknium1/hermes-miniverse GitHub: https://github.com/teknium1/hermes-miniverse Category: Integrations & Bridges Stars: 58 Bridge Hermes to Miniverse pixel worlds — agent embodiment in virtual environments Hermes-miniverse is a bridge that enables Hermes Agents to inhabit and interact within Miniverse pixel worlds. It functions through a three-part architecture consisting of a standalone bridge daemon, a gateway hook for state broadcasting, and a specific skill that allows the agent to consciously navigate the environment. This integration allows agents to maintain a visual presence, update their status in real-time, and engage in bidirectional communication with other AI entities. Users can deploy multiple bridges simultaneously to populate a virtual world with specialized Hermes instances. Highlights: - Connects Hermes Agents to Miniverse pixel-based virtual environments - Synchronizes live agent states including working, thinking, and idle - Enables bidirectional messaging between Hermes and other world agents --- ## Christabel337/job-scout-agent URL: https://hermesatlas.com/projects/Christabel337/job-scout-agent GitHub: https://github.com/Christabel337/job-scout-agent Category: Domain Applications Stars: 58 Autonomous job hunting — scans listings, writes cover letters, tracks applications Job Scout Agent is an autonomous tool that fetches job listings from multiple APIs and scores them against user skills and preferences. It performs company research and saves results into organized folders and a CSV tracker. Highlights: - Fetches jobs from live job board APIs - Scores listings against user skills and preferences - Updates a CSV tracker for Google Sheets --- ## solomon2773/nora URL: https://hermesatlas.com/projects/solomon2773/nora GitHub: https://github.com/solomon2773/nora Category: Deployment & Infra Stars: 58 Self-hosted control plane to deploy, monitor, and operate OpenClaw and Hermes AI agents on Docker/Kubernetes — with REST, CLI, and MCP. Nora is a self-hosted platform for deploying and operating OpenClaw and Hermes agent fleets on Docker or Kubernetes. It provides lifecycle controls, logs, monitoring, secrets management, workspaces, and access through a web interface, REST API, CLI, and MCP server. Highlights: - Supports Docker and Kubernetes deployments. - Includes searchable logs, metrics, and alert rules. - Provides REST API, CLI, and MCP server access. --- ## 0xarkstar/awesome-hermes-agent URL: https://hermesatlas.com/projects/0xarkstar/awesome-hermes-agent GitHub: https://github.com/0xarkstar/awesome-hermes-agent Category: Guides & Docs Stars: 57 Curated list of resources, tools, and projects for Hermes Agent by Nous Research. This project is a curated list of resources, tools, and projects for Hermes Agent, a self-improving AI agent by Nous Research. It includes links to official documentation, deployment options, skills, and various community integrations. Highlights: - Curated list of Hermes Agent resources - Includes deployment and skill integration links - Links to official Nous Research documentation --- ## zcweah1981/awesome-hermes-agent-zh URL: https://hermesatlas.com/projects/zcweah1981/awesome-hermes-agent-zh GitHub: https://github.com/zcweah1981/awesome-hermes-agent-zh Category: Guides & Docs Stars: 55 Chinese-language Hermes Agent hub: onboarding paths, local deployment guidance, OpenClaw migration notes, and troubleshooting references. This project provides a Chinese-language documentation hub and implementation guide for Hermes Agent. It offers structured paths for local deployment, domestic model integration in China, and migration from OpenClaw. Highlights: - Guides for integrating DeepSeek, Alibaba, Tencent, and other domestic models. - Documentation for multi-agent orchestration and MCP tool integration. - Troubleshooting references for installation, CLI, and gateway issues. --- ## amanning3390/flowstate-qmd URL: https://hermesatlas.com/projects/amanning3390/flowstate-qmd GitHub: https://github.com/amanning3390/flowstate-qmd Category: Memory & Context Stars: 52 Anticipatory memory with RAG and vector search — Hermes 2026 Hackathon entry FlowState-QMD is a local-first memory layer designed to provide coding agents with immediate project context from markdown documentation. It utilizes a SQLite-based vector store and an anticipatory cache that prefetches relevant documents by monitoring active agent session logs. This approach allows agents to access design docs, ADRs, and changelogs before initiating a reactive search loop. The system integrates via an MCP server and supports local execution using GGUF models and node-llama-cpp. Highlights: - Anticipatory cache prefetches context by watching agent session logs - Local-first storage using SQLite-vec and GGUF models via node-llama-cpp - MCP-native server with automated configuration for major coding agent clients --- ## Ridwannurudeen/hermes-council URL: https://hermesatlas.com/projects/Ridwannurudeen/hermes-council GitHub: https://github.com/Ridwannurudeen/hermes-council Category: Integrations & Bridges Stars: 52 Adversarial multi-perspective council MCP server for decision-making Hermes Council is an MCP server designed to provide an adversarial judgment layer for Hermes Agent to prevent overconfident or unsafe autonomous actions. It functions by employing multiple specialized personas—such as Advocate, Skeptic, and Arbiter—to deliberate on plans, code diffs, and claims. This structured deliberation produces explicit verdicts including risk assessments, required checks, and verified evidence. The toolset also supports RL workflows by extracting DPO preference pairs and normalized rewards. Highlights: - Provides adversarial preflight reviews for high-stakes autonomous actions - Stress-tests implementation plans and code diffs for potential failures - Generates structured verdicts and DPO preference pairs for RL training --- ## FahrenheitResearch/hermes-weather-plugin URL: https://hermesatlas.com/projects/FahrenheitResearch/hermes-weather-plugin GitHub: https://github.com/FahrenheitResearch/hermes-weather-plugin Category: Plugins & Extensions Stars: 49 NWS-grade model imagery, NEXRAD radar, and verified meteorological calculations. Pure Rust. The Hermes Weather Plugin provides a suite of 13 meteorological tools for the Hermes Agent ecosystem, enabling real-time access to observations, forecasts, and high-fidelity model imagery. It utilizes a Python-first architecture that offloads heavy computational tasks, such as NEXRAD radar rendering and ECAPE calculations, to high-performance Rust backends. The plugin features an automated bootstrap process that compiles necessary Rust binaries on first use, ensuring a streamlined setup for complex weather analysis. Users can retrieve verified model soundings, severe weather outlooks from the SPC, and global data via Open-Meteo integration. Highlights: - Thirteen tools for NWS forecasts, radar imagery, and severe weather alerts - Rust-backed meteorological calculations for ECAPE, soundings, and parcel profiles - Automated bootstrap system for compiling and caching required Rust binaries --- ## amanning3390/hermeshub URL: https://hermesatlas.com/projects/amanning3390/hermeshub GitHub: https://github.com/amanning3390/hermeshub Category: Skills & Skill Registries Stars: 48 Community skill browsing, search, and one-click installation hub HermesHub is an ARD-compliant agent registry that enables the discovery and indexing of AI agent capabilities. It utilizes a Hermes Agent to autonomously crawl, validate, and index manifests hosted at /.well-known/ai-catalog.json endpoints. Users can list agents for free via self-publishing or through a paid hosted listing that includes health checks. The platform supports ranked discovery via a standardized search API and maintains federation with Hugging Face Discover and GitHub Agent Finder. Highlights: - Full implementation of Agentic Resource Discovery (ARD) v0.9 specification - Autonomous 24/7 operation via Hermes Agent on NVIDIA infrastructure - Federated search integration with GitHub and Hugging Face --- ## xmbshwll/hermes-agent-docker URL: https://hermesatlas.com/projects/xmbshwll/hermes-agent-docker GitHub: https://github.com/xmbshwll/hermes-agent-docker Category: Deployment & Infra Stars: 48 Simple Docker sandbox image for Hermes Agent This project provides a minimal Docker sandbox image designed to package and deploy Hermes Agent. It utilizes the official upstream installation script to set up the agent and includes mini-swe-agent within the container. The image supports multi-arch publishing and allows for persistent state management by mounting the agent's home directory. Users can easily build specific versions using build arguments to target different Hermes branches or tags. Highlights: - Includes mini-swe-agent and official Hermes installation - Supports persistent state via mounted home directories - Allows building specific Hermes tags using build arguments --- ## yepyhun/Brainstack URL: https://hermesatlas.com/projects/yepyhun/Brainstack GitHub: https://github.com/yepyhun/Brainstack Category: Memory & Context Stars: 48 Memory kernel stack for Hermes agent Brainstack is a local-first memory kernel for Hermes agents that replaces flat memory storage with a composite provider model. It organizes information into distinct shelves for profiles, session continuity, temporal graph truth, and corpus retrieval to prevent prompt flooding and maintain factual consistency. Highlights: - Integrates Hindsight, Graphiti, and MemPalace into a single memory owner. - Uses SQLite, Kuzu, and Chroma for state and retrieval management. - Provides a purpose-built evidence packet to the agent per query. --- ## nujovich/hermes-telemetry URL: https://hermesatlas.com/projects/nujovich/hermes-telemetry GitHub: https://github.com/nujovich/hermes-telemetry Category: Plugins & Extensions Stars: 48 Budget enforcement + observability plugin for Hermes Agent. Stops runaway costs before they happen. hermes-telemetry is a Hermes Agent plugin that records API and tool-call usage, including tokens, estimated cost, and latency. It enforces budget limits by notifying at a soft limit and blocking further tool calls at a hard limit; a breached cron-job budget also pauses that job. Highlights: - Records usage in SQLite with WAL mode. - Provides `/stats`, `/budget`, and `/setup` surfaces. - Automatically syncs OpenRouter pricing. --- ## 0xrsydn/nix-hermes-agent URL: https://hermesatlas.com/projects/0xrsydn/nix-hermes-agent GitHub: https://github.com/0xrsydn/nix-hermes-agent Category: Deployment & Infra Stars: 46 Nix package and NixOS module for reproducible Hermes deployment nix-hermes-agent provides a Nix package and NixOS module for the declarative deployment of Hermes Agent. It allows users to manage the entire agent lifecycle—including configurations, workspace documents, and systemd services—through a single Nix configuration file. The module features a robust update policy that uses quarantined candidate pull requests to prevent broken upstream releases from affecting stable deployments. It also supports secure secrets management by keeping API keys and authentication tokens outside of the Nix store. Highlights: - Declarative configuration for cli-config.yaml and workspace documents - Hybrid skill management supporting both Nix-managed and CLI-installed skills - Secure secrets integration via systemd EnvironmentFiles and sops-nix --- ## willingning-coder/eagle-eye URL: https://hermesatlas.com/projects/willingning-coder/eagle-eye GitHub: https://github.com/willingning-coder/eagle-eye Category: Skills & Skill Registries Stars: 44 5-layer intelligent skill retrieval for Hermes Agent with hard triggers, FTS5, synonyms, dense embeddings, and RRF fusion. Eagle Eye is a plugin for Hermes Agent designed to optimize skill selection by filtering large skill libraries into a small set of relevant candidates. It utilizes a five-layer retrieval architecture that combines deterministic keyword triggers, FTS5 text similarity, synonym matching, and dense semantic embeddings via RRF fusion. This approach reduces token consumption and prevents LLM confusion by providing only the most relevant skill hints rather than the entire list. Highlights: - Five-layer retrieval including hard triggers and semantic embeddings - Reduces token usage by narrowing skill lists before LLM calls - Graceful degradation if embedding models or dependencies are missing --- ## xiaonancs/hermes-agent-study URL: https://hermesatlas.com/projects/xiaonancs/hermes-agent-study GitHub: https://github.com/xiaonancs/hermes-agent-study Category: Guides & Docs Stars: 42 Chinese deep research series on Hermes Agent internals, OpenClaw lineage, self-evolution, and source-code architecture This project provides a comprehensive technical analysis and documentation series focused on the internal architecture of the Hermes Agent by Nous Research. It breaks down the system's core components, including its Python-based execution loop, tool registry, and self-evolution engine, while providing nearly 100 architectural diagrams. The research also explores the project's lineage by comparing its structure to OpenClaw and investigating claims regarding its EvoMap-inspired self-improvement logic. Additionally, it tracks rapid version iterations from v0.9.0 to v0.14.0, covering new features like the Transport ABC and autonomous curators. Highlights: - Deep source-code analysis of Hermes Agent architecture and evolution engine - Comparative studies against OpenClaw, EvoMap, and other Agent frameworks - Detailed documentation of memory systems, skill hubs, and tool registries --- ## metantonio/hermes-wsl-ubuntu URL: https://hermesatlas.com/projects/metantonio/hermes-wsl-ubuntu GitHub: https://github.com/metantonio/hermes-wsl-ubuntu Category: Guides & Docs Stars: 42 Step-by-step WSL2 Ubuntu setup guide for Windows users This project provides a comprehensive guide and automation scripts for deploying the Hermes Agent with llama.cpp and Qwen3.5 on local environments. It facilitates the end-to-end setup of an AI agent stack including GPU acceleration via CUDA for Linux/WSL2 or Metal for macOS. The workflow integrates Camofox for browser automation and Hermes HUDUI for a graphical web interface. Highlights: - Automated installation scripts for Ubuntu/WSL2 and macOS - Supports GPU acceleration via CUDA and Metal backends - Integrates Camofox browser server and Hermes HUDUI --- ## indranilbanerjee/socialforge URL: https://hermesatlas.com/projects/indranilbanerjee/socialforge GitHub: https://github.com/indranilbanerjee/socialforge Category: Plugins & Extensions Stars: 42 Open-source agency-grade social media production plugin — 16 skills, 25 commands, AI image (Nano Banana Pro) + AI video (Kling v3.0 Pro) + C2PA signing (EU AI Act Article 50). Installs on Claude Code, SocialForge automates monthly social media calendars by parsing content, matching brand assets, creating visuals, adapting copy for platforms, and preparing review galleries and delivery documents. It supports AI image generation with Vertex AI, AI video generation with WaveSpeed, and C2PA signing before review; paid generation requires a price quote and user approval. Highlights: - Adapts copy for Instagram, TikTok, LinkedIn, Threads, X, Facebook, and YouTube Shorts - Keeps brand photos pixel-faithful during asset-first compositing - Pauses for client review before packaging delivery --- ## generalbusiness-ai/keep URL: https://hermesatlas.com/projects/generalbusiness-ai/keep GitHub: https://github.com/generalbusiness-ai/keep Category: Memory & Context Stars: 41 Reflective memory for AI agents Keep is a reflective memory system for AI agents that facilitates long-term learning and contextual awareness. It processes diverse inputs—including URLs, codebases, and multimedia—by summarizing, embedding, and organizing them into a searchable graph. The system uses 'edge tags' to create navigable relationships between notes, such as linking speakers to transcripts or commits to files. It integrates directly with Hermes Agent and other MCP-compatible tools to help agents track intentions and reflect on past actions. Highlights: - Semantic search with BM25 full-text and ranked graph traversal - Automated indexing for codebases, URLs, and multimedia with OCR support - Edge tags create navigable, bidirectional relationships between stored notes --- ## aliasocracy/hermes-tool-slimmer URL: https://hermesatlas.com/projects/aliasocracy/hermes-tool-slimmer GitHub: https://github.com/aliasocracy/hermes-tool-slimmer Category: Memory & Context Stars: 41 Reduce Hermes Agent tool-schema overhead with keyword selection and Tool Search support Hermes Tool Slimmer is a plugin for Hermes Agent designed to reduce the token overhead of model requests by trimming tool schemas. It uses BM25 ranking to select relevant tools based on the user's request while maintaining a fallback mechanism for the model to request the full tool catalog. Highlights: - Reduces tool schema tokens using local keyword-based ranking. - Integrates via middleware without patching Hermes core on version 0.19+. - Includes a dashboard for monitoring savings and managing tool configurations. --- ## hermes-labs-ai/little-canary URL: https://hermesatlas.com/projects/hermes-labs-ai/little-canary GitHub: https://github.com/hermes-labs-ai/little-canary Category: Plugins & Extensions Stars: 41 Detects prompt injection by its effect on a sacrificial canary model, not just pattern matching: untrusted input hits a powerless model first, a behavioral check reads the residue, and it returns bloc Little Canary screens untrusted text by sending it to a powerless canary model and checking whether the input changed its behavior. It returns PASS, FLAG, or BLOCK verdicts for a host to enforce, and also runs structural checks for known suspicious patterns. Highlights: - StructuralFilter checks known patterns without a model or network call. - Live canary screening can use a local model through Ollama. - The project publishes evaluation corpora and reproduction commands. --- ## cablate/Agentic-MCP-Skill URL: https://hermesatlas.com/projects/cablate/Agentic-MCP-Skill GitHub: https://github.com/cablate/Agentic-MCP-Skill Category: Skills & Skill Registries Stars: 40 Progressive MCP client with three-layer lazy loading — validates agentskills.io pattern Agentic-MCP-Skill is an experimental MCP client designed to reduce token consumption through a three-layer progressive disclosure pattern. It implements a socket-based daemon architecture that allows AI agents to load server metadata, tool lists, and specific tool schemas incrementally rather than all at once. This approach aims to optimize context window usage and improve the efficiency of managing multiple MCP servers. Highlights: - Three-layer progressive loading to minimize token usage - Socket-based daemon architecture for persistent connections - Incremental discovery of server metadata and tool schemas --- ## 0xNyk/openclaw-to-hermes URL: https://hermesatlas.com/projects/0xNyk/openclaw-to-hermes GitHub: https://github.com/0xNyk/openclaw-to-hermes Category: Developer Tools Stars: 40 Migration tool from OpenClaw to Hermes Agent openclaw-to-hermes is a Python-based migration tool designed to transfer agents, workspaces, and configurations from OpenClaw to Hermes Agent. It maps model settings, credentials, and markdown-based memories while creating backups and supporting dry-run previews. Highlights: - Migrates SOUL.md, MEMORY.md, skills, and memory archives to Hermes. - Maps OpenClaw configs and credentials into Hermes YAML and JSON formats. - Sets up systemd gateway services and handles nested auth structures. --- ## pengchengxia75-arch/hermes-agent-windows URL: https://hermesatlas.com/projects/pengchengxia75-arch/hermes-agent-windows GitHub: https://github.com/pengchengxia75-arch/hermes-agent-windows Category: Forks & Derivatives Stars: 38 Windows-native Hermes Agent adaptation with one-line PowerShell installer and no WSL requirement This project is a Windows-native adaptation of the Hermes Agent that eliminates the need for WSL2 or Linux environments. It utilizes a PowerShell-based installer to deploy the agent directly into the Windows ecosystem while resolving platform-specific issues like process signal handling. The fork introduces a dedicated Web UI management panel for real-time chat, session history, and visual configuration of skills and API keys. Highlights: - Native Windows installation via a one-line PowerShell script - Eliminates WSL2 requirement for running Hermes Agent - Integrated Web UI for chat, logs, and token usage analytics --- ## Sahil-SS9/hermaguard URL: https://hermesatlas.com/projects/Sahil-SS9/hermaguard GitHub: https://github.com/Sahil-SS9/hermaguard Category: Skills & Skill Registries Stars: 38 Adversarial bug-hunting code review for AI agents. 3 parallel subagents attack code from different angles, then a consolidator merges and triages findings. Read-only — finds problems, doesn't fix. HermaGuard v2.1.0 is a read-only adversarial bug-hunting tool for AI agents that uses a deterministic pre-scan followed by three parallel subagents to identify code vulnerabilities. It features a verification sandbox for proof-of-concept execution and a consolidator that triages findings into markdown and JSON reports. Highlights: - Parallel subagents for edge cases, adversarial review, and integration analysis. - Deterministic pre-scan using semgrep, bandit, eslint, gosec, and ruff. - Verified findings via proof-of-concept execution in a hardened sandbox. --- ## Xquik-dev/hermes-tweet URL: https://hermesatlas.com/projects/Xquik-dev/hermes-tweet GitHub: https://github.com/Xquik-dev/hermes-tweet Category: Plugins & Extensions Stars: 37 Native Hermes Agent plugin for X automation through Xquik Hermes Tweet adds Twitter search, reads, monitoring, and X actions to Hermes Agent through Xquik. It includes separate tools for reads and actions, with actions disabled by default, plus a bundled Hermes Skill and two slash commands. Highlights: - Search X posts and read profile timelines. - Actions include extraction, monitoring, posting, and replying. - Slash commands show account status and current X trends. --- ## EntangledQuantum/Life_OS URL: https://hermesatlas.com/projects/EntangledQuantum/Life_OS GitHub: https://github.com/EntangledQuantum/Life_OS Category: Skills & Skill Registries Stars: 37 ADHD-friendly personal execution OS: habits, study blocks, agent control (Hermes/MCP), local SQLite Life OS is a personal app where an AI agent creates and maintains habits, schedules tasks, tracks goals, and adjusts plans based on what happened. Users tap to complete items, while data stays in a local SQLite file with no account or cloud sync. Highlights: - Habits recur and are scored daily; tasks cover other activities. - Includes an Android client and connects to agents over MCP. - Runs locally and stores data in SQLite. --- ## JackTheGit/hermes-ai-infrastructure-monitoring-toolkit URL: https://hermesatlas.com/projects/JackTheGit/hermes-ai-infrastructure-monitoring-toolkit GitHub: https://github.com/JackTheGit/hermes-ai-infrastructure-monitoring-toolkit Category: Domain Applications Stars: 35 Autonomous monitoring — cron-based research ingestion, cost forecasting, headless systemd This project is a reference implementation for building autonomous, long-running monitoring systems using Hermes Agent. It utilizes cron-based workflows to ingest AI research from arXiv and track infrastructure repositories on GitHub. The system automatically generates structured markdown reports covering compute risk analysis, cost projections, and trend dashboards. It serves as a template for developers to deploy headless, scheduled agents that transform raw research data into actionable infrastructure intelligence. Highlights: - Automated research ingestion via arXiv API and GitHub ecosystem tracking - Scheduled cron workflows for risk analysis and cost modeling - Generates terminal-style dashboards and structured markdown intelligence reports --- ## indranilbanerjee/contentforge URL: https://hermesatlas.com/projects/indranilbanerjee/contentforge GitHub: https://github.com/indranilbanerjee/contentforge Category: Plugins & Extensions Stars: 32 Open-source enterprise content production plugin — 21 skills, 13 agents, 11 quality gates, 29-pattern AI humanizer, fact-checker, real .docx output with C2PA signing (EU AI Act Article 50 ready). Inst ContentForge is an open-source content production plugin that runs a 10-phase pipeline to produce publication-ready .docx files with fact-checking, internal linking, and C2PA provenance. It includes a humanizer, a run auditor that re-derives quality gates, and a lifecycle loop for measuring and auditing published content. It installs on Claude Code, Cowork, Codex, Cursor, Copilot CLI, and other agent platforms. Highlights: - 10-phase pipeline with script-checked quality gates - Outputs .docx with C2PA provenance sidecar - Requires typed yes before publishing or translating --- ## conorbronsdon/agent-context-os URL: https://hermesatlas.com/projects/conorbronsdon/agent-context-os GitHub: https://github.com/conorbronsdon/agent-context-os Category: Memory & Context Stars: 30 A Git-backed context and workflow layer for Claude Code, Codex, and compatible coding agents. Context OS keeps durable project context and workflows in a Git-backed repository of Markdown files. Its adapters let supported coding agents use shared repository state, while reviewed setup, checkpoint, and close requests produce proposals and receipts. Highlights: - Supports adapters for Claude Code, Codex, and other listed agents. - Includes workflows for migration, handoffs, and memory proposals. - Integrations are opt-in and are not enabled automatically. --- ## CorsenAI/hermes-connector URL: https://hermesatlas.com/projects/CorsenAI/hermes-connector GitHub: https://github.com/CorsenAI/hermes-connector Category: Plugins & Extensions Stars: 29 Chrome browser extension for Hermes Agent — exact sessions, user-selected tabs, and local-first browser control. Hermes Connector is an open-source Chrome extension that links a selected Hermes profile and session to Chrome tabs you choose. From Chrome’s side panel, you can attach tabs and let Hermes read or control them; version 0.2.4 can also discover Hermes Desktop sessions. Highlights: - Only attached tabs are available to the selected Hermes session. - Supports page interaction, tab controls, and requested screenshots. - The extension and companion must use matching versions. --- ## FPSUnleashed/hermes-codex-skin URL: https://hermesatlas.com/projects/FPSUnleashed/hermes-codex-skin GitHub: https://github.com/FPSUnleashed/hermes-codex-skin Category: Plugins & Extensions Stars: 29 Codex Skin: a self-contained Codex-inspired visual layer for Hermes Desktop. Codex Skin adds a Codex-inspired chat layout to Hermes Desktop, with native theme colors, Glass/Clear backgrounds, history previews, and an optional task Inbox. It offers adjustable composer width and transcript settings; Hermes retains ownership of model menus, voice controls, and Queue behavior. Highlights: - Inbox can settle or snooze threads without stopping their work. - Settings persist locally. - Disable the plugin to restore Hermes’ normal appearance. --- ## jpalmae/hermeshq URL: https://hermesatlas.com/projects/jpalmae/hermeshq GitHub: https://github.com/jpalmae/hermeshq Category: Deployment & Infra Stars: 28 HermesHQ is a Docker-first control plane for running and operating multiple Hermes Agent instances from one web application. HermesHQ is a Docker-based control plane designed to orchestrate and manage multiple Hermes Agent instances through a centralized web application. It provides an operational layer for the Hermes runtime, featuring task dispatch, multi-agent delegation, and administrative controls such as RBAC and permission policies. Highlights: - Orchestrates multiple managed agents with separate workspaces and identities. - Provides per-agent Telegram and WhatsApp communication channels. - Enforces granular tool, path, and network permission policies. --- ## vectrocomputers/Hermes-Agent-Action-Plan URL: https://hermesatlas.com/projects/vectrocomputers/Hermes-Agent-Action-Plan GitHub: https://github.com/vectrocomputers/Hermes-Agent-Action-Plan Category: Guides & Docs Stars: 25 Privacy-first practical guidance for configuring and operating Hermes Agent effectively The Hermes Agent Action Plan is a configuration framework and operational guide designed to optimize Hermes Agent deployments on Ubuntu 24. It provides a structured philosophy for setting up an autonomous assistant that prioritizes local-first tools, persistent memory, and granular system access. By implementing specific security hardening, firewall rules, and communication guidelines, the plan enables the agent to perform complex tasks while maintaining user privacy and auditability. The guide serves as a template for transitioning the agent from a basic chatbot into a capable system administrator or personal assistant. Highlights: - Privacy-first configuration prioritizing local and open-source tools - Structured memory system using daily logs and long-term curated files - Security-focused system access strategy with audit trails and recovery steps --- ## Ladybug-Memory/hermes-memory-plugin URL: https://hermesatlas.com/projects/Ladybug-Memory/hermes-memory-plugin GitHub: https://github.com/Ladybug-Memory/hermes-memory-plugin Category: Memory & Context Stars: 24 Local-only Hermes memory plugin with built-in 1-10 importance ranking so the things that matter most surface first. Columnar .lbdb embedded graph DB, BM25-first retrieval, optional GLiNER2 entity extraction. Hermes Ladybug Memory is a local-first memory provider plugin that enables Hermes agents to store and retrieve information without relying on cloud services or external APIs. It utilizes a columnar embedded graph database to manage typed memory entries, named relationships, and importance-weighted recall. The system prioritizes high-value information using a 1-10 importance scale and supports BM25 keyword search for precise retrieval. Users can also enable optional entity extraction via GLiNER2 to build structured knowledge graphs directly on their local machine. Highlights: - Local-only storage using a single .lbdb embedded graph database file - Importance-weighted recall surfaces high-priority memories during context prefetch - Supports BM25 keyword search and named graph relationships between entries --- ## Capslockb/hermes-live-discord-agent-plugin URL: https://hermesatlas.com/projects/Capslockb/hermes-live-discord-agent-plugin GitHub: https://github.com/Capslockb/hermes-live-discord-agent-plugin Category: Plugins & Extensions Stars: 24 Hermes Live Discord Agent Plugin — full-duplex Discord voice ↔ Google Gemini Multimodal Live API, with function calling, idle hangup, transcripts, and a 3-min oneshot installer. Hermes Live is a self-hosted Hermes Agent plugin that connects Discord voice channels to the Google Gemini Multimodal Live API. It enables real-time voice conversation and supports optional tool integrations and notifications. Highlights: - Full-duplex Discord voice input and output - Supports Gemini Multimodal Live sessions - Provides JSONL voice-event records --- ## Sahil-SS9/hermes-simplify-swarm URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-simplify-swarm GitHub: https://github.com/Sahil-SS9/hermes-simplify-swarm Category: Skills & Skill Registries Stars: 22 Multi-agent code simplification skill for Hermes Agent. 3 parallel sub-agents (Hygiene, Clarity, Correctness) with risk-tiered application. Inspired by Claude Code's /simplify. Simplify Swarm is a multi-agent skill for code simplification that uses three parallel, read-only agents to analyze git diffs. The system categorizes findings into SAFE, CAREFUL, and RISKY tiers and requires user approval before applying changes. Highlights: - Uses Hygiene, Clarity, and Correctness agents - Supports TypeScript, JavaScript, Python, Go, and Rust - Features a tiered application process with an approval gate --- ## Sahil-SS9/Toolaria URL: https://hermesatlas.com/projects/Sahil-SS9/Toolaria GitHub: https://github.com/Sahil-SS9/Toolaria Category: Plugins & Extensions Stars: 22 Rescue oversized tool results before they flood context. SHA256-addressed blob store with per-session indexes Toolaria is a single-purpose Hermes Agent plugin that stores oversized MCP or web tool results in a SHA256-addressed blob store and returns a compact excerpt with a fetch handle. The model can retrieve selected slices using `rescuer_fetch`, inspect structural outlines, search content, or pass the full result to another tool by reference. Highlights: - Rescues oversized tool results before they enter the context window. - Supports outline, search, range, grep, stat, and full fetch modes. - Passes stored results to downstream tools using `tla:`. --- ## Jezue/fitatu_library URL: https://hermesatlas.com/projects/Jezue/fitatu_library GitHub: https://github.com/Jezue/fitatu_library Category: Integrations & Bridges Stars: 21 Unofficial Python API client for Fitatu — built for AI agents and automation fitatu-api is an unofficial Python client for Fitatu that can read and update food diaries, activities, body measurements, water, goals, summaries, and food catalog data. It also provides tools for AI agents and an MCP server that makes those tools available to MCP hosts. Highlights: - Includes 47 tools for Fitatu diary operations. - MCP server supports stdio and HTTP. - Requires Python 3.11 or newer. --- ## Sahil-SS9/hermes-Custom-CLI-Themes URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-Custom-CLI-Themes GitHub: https://github.com/Sahil-SS9/hermes-Custom-CLI-Themes Category: Plugins & Extensions Stars: 20 Custom YAML skin pack for the Hermes Agent CLI with themed palettes, spinners, branding, and ASCII banners. Hermes Custom CLI Themes is a collection of visual skins designed to personalize the Hermes Agent terminal interface. Each theme is defined in a single YAML file that configures color palettes, spinners, branding, and ASCII banner art. Users can apply these skins by placing them in a specific local directory and updating their configuration or using an in-app command. The project includes a variety of themed presets ranging from tactical and sci-fi aesthetics to minimalist investigator styles. Highlights: - Provides YAML-based skins for terminal palettes and ASCII branding. - Includes a one-liner script for automated skin installation. - Supports custom extended keys for advanced UI element styling. --- ## MilkyWay008/Hermes-OTG URL: https://hermesatlas.com/projects/MilkyWay008/Hermes-OTG GitHub: https://github.com/MilkyWay008/Hermes-OTG Category: Deployment & Infra Stars: 20 Your agentic system rescue companion, especially for broken host Hermes. Hermes Agent on a USB stick — zero install & portable, hot-swappable & instant full agent power on any PC. Hermes OTG is a portable, zero-install version of the Hermes Agent designed for Windows 10 and 11. It operates from any drive or folder using relative paths to avoid host system pollution and can run side-by-side with an installed Hermes instance using a separate port and data directory. Highlights: - Runs from USB or any drive without host installation or registry writes. - Includes Desktop, TUI, and Gateway modes with isolated data environments. - Bundles Python 3.12, PortableGit, and Sysinternals rescue tools for offline use. --- ## carterwayneskhizeine/hermes-agent-windows-R URL: https://hermesatlas.com/projects/carterwayneskhizeine/hermes-agent-windows-R GitHub: https://github.com/carterwayneskhizeine/hermes-agent-windows-R Category: Forks & Derivatives Stars: 19 Windows-native adaptation fork of Hermes Agent with runtime, path, process, and terminal backend compatibility improvements This project is a Windows-native fork of Hermes Agent designed to resolve compatibility issues with path handling, process management, and terminal encoding. It implements specific adaptations for Git Bash path conversion and introduces a multi-profile runtime system for running parallel instances. The fork includes a dedicated PowerShell-based startup workflow and a web-based Dashboard UI optimized for the Windows environment. Highlights: - Fixes Git Bash path handling and terminal encoding for Windows - Supports multi-profile management and parallel gateway instances - Includes psmux integration for one-click automated environment launching --- ## JackTheGit/hermes-autonomous-server URL: https://hermesatlas.com/projects/JackTheGit/hermes-autonomous-server GitHub: https://github.com/JackTheGit/hermes-autonomous-server Category: Deployment & Infra Stars: 19 Headless systemd deployment with Nous Portal integration — production-ready This project provides a deployment framework for running Hermes Agent as a persistent, headless Linux service. It utilizes systemd to manage the Hermes Gateway, ensuring the agent remains active across reboots without requiring an open terminal session. The setup integrates with the Nous Portal for model access and leverages the native Hermes cron scheduler to automate recurring AI tasks. This approach offers a stable, self-hosted alternative to manual shell loops or third-party hosting for autonomous server operations. Highlights: - Configures Hermes Gateway as a reboot-safe systemd service - Enables autonomous execution of recurring AI cron jobs - Supports headless operation on Ubuntu and Debian servers --- ## handnewb/hermes-cybersec-lab URL: https://hermesatlas.com/projects/handnewb/hermes-cybersec-lab GitHub: https://github.com/handnewb/hermes-cybersec-lab Category: Skills & Skill Registries Stars: 19 🛡️ Turnkey cybersecurity lab for Hermes Agent — 397 CVE-driven skills, 152 tools, 28 frameworks (MITRE ATT&CK, MISP, CVSS, EPSS, OWASP, NIST, Sigma, YARA). Real exploits 2015–2026. Hermes Cybersecurity Lab is a turnkey ecosystem designed for the Hermes Agent. It provides a collection of 2,077 skills, 131+ tools, and 28 cybersecurity frameworks across eight repositories. Highlights: - Includes 2,077 total skills across multiple repositories - Installs 131+ tools for network, forensics, and exploitation - Integrates 28 cybersecurity frameworks and standards --- ## 42-evey/evey-bridge-plugin URL: https://hermesatlas.com/projects/42-evey/evey-bridge-plugin GitHub: https://github.com/42-evey/evey-bridge-plugin Category: Plugins & Extensions Stars: 18 Claude Code and Hermes context sharing bridge — auto-checks messages, Mother Mode loop The Evey Bridge Plugin is a technical integration that connects Claude Code with the Evey hermes-agent stack. It functions by automatically checking for messages or tasks from the bridge and injecting them as context into every prompt submission. The plugin includes specialized commands for running a 'Mother Mode' improvement loop and monitoring system health, including wallet and cron status. It is designed specifically for users running the Evey stack at a designated local directory. Highlights: - Injects Evey messages and tasks into Claude Code prompts - Automates Mother Mode improvement loops via the /evey-loop command - Monitors health, wallets, and crons with quick status checks --- ## martymcenroe/HermesWiki URL: https://hermesatlas.com/projects/martymcenroe/HermesWiki GitHub: https://github.com/martymcenroe/HermesWiki Category: Guides & Docs Stars: 18 Community wiki with deployment patterns and recipes HermesWiki provides documentation for Hermes, an autonomous email agent that triages inbound recruiter outreach. The wiki covers the system's architecture, conversation state machine, guardrails, evaluation, security, and cost engineering. Highlights: - Covers threat modeling against OWASP and MITRE frameworks - Includes NIST alignment and cost breakdowns --- ## Sahil-SS9/hermes-memlock URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-memlock GitHub: https://github.com/Sahil-SS9/hermes-memlock Category: Plugins & Extensions Stars: 18 Re-assert standing instructions after context compaction. Pin anchors, detect drift, rehydrate before the model forgets MemLock is a plugin for the Hermes ecosystem designed to prevent instruction decay following context compaction. It detects compaction events, audits whether pinned instructions remain in the active context region, and rehydrates missing instructions as a reminder block. Highlights: - Detects Hermes context compaction markers to identify instruction drift. - Audits active context regions for pinned anchors using keyword probes. - Rehydrates drifted instructions only when they are missing from active memory. --- ## hxsteric/mercury URL: https://hermesatlas.com/projects/hxsteric/mercury GitHub: https://github.com/hxsteric/mercury Category: Domain Applications Stars: 17 Blockchain cash flow analyzer — multi-chain analysis, fraud detection, WebGL dashboard Mercury is a blockchain cash flow analyzer and Hermes Agent skill designed to provide transparency into wallet activities across Ethereum, Base, and Solana. It utilizes parallel subagents to fetch transaction data, identify six specific fraud patterns, and generate AI-driven trading strategies based on wallet behavior. The project features a multi-layer WebGL and Canvas dashboard for real-time visualization of inflows, outflows, and risk metrics. It operates as a standalone tool or an integrated Hermes skill for automated multi-chain investigations. Highlights: - Analyzes transaction flows across Ethereum, Base, and Solana chains - Detects six fraud patterns including mixer interactions and dust attacks - Visualizes data via interactive WebGL and Canvas-based dashboards --- ## rodmarkun/anihermes URL: https://hermesatlas.com/projects/rodmarkun/anihermes GitHub: https://github.com/rodmarkun/anihermes Category: Domain Applications Stars: 16 Local anime server and tracker via natural language for Hermes Agent AniHermes is a natural language media server that simplifies the process of downloading and tracking anime. It leverages the Hermes Agent for LLM-driven tool orchestration to manage library tasks through conversational interfaces on Telegram, Discord, or the CLI. The system integrates with qbittorrent for downloads and Anilist for watchlist synchronization. Users can perform complex actions like identifying anime from screenshots via vision analysis or scheduling automatic weekly downloads. Highlights: - Natural language control via Telegram, Discord, and CLI - Automated downloads using qbittorrent and Anilist synchronization - Vision-based anime identification from uploaded screenshots --- ## bryercowan/hermes-embodied URL: https://hermesatlas.com/projects/bryercowan/hermes-embodied GitHub: https://github.com/bryercowan/hermes-embodied Category: Domain Applications Stars: 16 Self-improving robotics via VLA model fine-tuning on cloud GPUs Hermes Embodied is a robotics extension for Hermes Agent that enables autonomous fine-tuning of Vision-Language-Action (VLA) models through natural language. The system orchestrates a self-improvement loop by collecting robot trajectories in simulation or hardware, provisioning cloud GPUs via Vast.ai, and retraining models when performance thresholds are met. It integrates with the LeRobot framework and MuJoCo simulation to automate the transition from data collection to model promotion. This allows users to manage complex robotics training pipelines without manual machine learning expertise. Highlights: - Automates VLA fine-tuning loops using natural language commands - Provisions and manages Vast.ai cloud GPU instances autonomously - Supports SmolVLA and GR00T models for simulation or physical hardware --- ## beardthelion/hermes-skill-distillation URL: https://hermesatlas.com/projects/beardthelion/hermes-skill-distillation GitHub: https://github.com/beardthelion/hermes-skill-distillation Category: Forks & Derivatives Stars: 16 Generate agentic training trajectories from real-world tasks for Hermes 4 fine-tuning This project provides a skill distillation pipeline designed to fine-tune Hermes 4 models using real-world agentic trajectories. It captures tool-use sessions from a diverse 30-task battery and converts them into SFT-ready data or live RL signals for the Atropos training framework. The system uses a multi-dimensional reward function to score trajectories based on task completion, efficiency, and error recovery. This approach enables a closed learning loop where production-style agent interactions serve as the primary training data for future model iterations. Highlights: - Generates SFT-ready JSONL data from real-world tool usage trajectories - Integrates with Atropos for live reinforcement learning via GRPO - Automated scoring based on completion, efficiency, and error recovery --- ## Context4GPTs/klodi-plugin URL: https://hermesatlas.com/projects/Context4GPTs/klodi-plugin GitHub: https://github.com/Context4GPTs/klodi-plugin Category: Plugins & Extensions Stars: 16 The agent-to-agent marketplace, in your agent host. Your agent lists, haggles, and closes deals for you while you live your life. klodi is an Agent2Agent marketplace designed for AI agents to list, haggle, and close deals. It provides adapters for various agent hosts to enable agent-led negotiations and transactions. Highlights: - Supports multiple host adapters including OpenClaw, Hermes, and Moltis - Uses on-disk strategies to manage identity and ratings - Facilitates a lifecycle of listings, offers, channels, and transactions --- ## teixeirazeus/fablize-for-hermes URL: https://hermesatlas.com/projects/teixeirazeus/fablize-for-hermes GitHub: https://github.com/teixeirazeus/fablize-for-hermes Category: Skills & Skill Registries Stars: 16 This project adapts fablize's verified procedures — verification grounding, multi-story evidence gating, investigation protocol, and early-stop prevention. fablize-for-hermes is a port of the fablize procedure system designed to improve task completion and verification within the Hermes Agent ecosystem. It implements a structured behavioral ruleset that enforces multi-step task decomposition, evidence-based checkpoints, and systematic investigation protocols for debugging. By utilizing a Python-based goal engine and specific verification packs, the project ensures agents ground their claims in tool results rather than ending tasks prematurely. This framework helps maintain procedural discipline during complex coding, UI rendering, and logic tasks. Highlights: - Implements multi-story task decomposition with mandatory evidence-based verification gates. - Provides a systematic investigation protocol for reproduction and causal debugging. - Includes a Python goal engine for persistent task state management. --- ## Heybinshao/hermes-appearance-hub URL: https://hermesatlas.com/projects/Heybinshao/hermes-appearance-hub GitHub: https://github.com/Heybinshao/hermes-appearance-hub Category: Plugins & Extensions Stars: 16 Hermes Desktop 外观整合插件：纸纹 + 霞鹜文楷字体，状态栏一键开关 Hermes Appearance Hub is a Hermes desktop plugin that gathers appearance and conversation-behavior settings in a status-bar panel. It includes theme and language controls, paper texture simulation, LXGW WenKai font support, interface scaling, and other settings that take effect immediately and sync with the official settings page. Highlights: - Provides a floating appearance panel opened from the status bar. - Includes 14 themes, language controls, paper texture, and font toggles. - Removes injected changes and restores official settings when disabled or removed. --- ## PederHP/skillsdotnet URL: https://hermesatlas.com/projects/PederHP/skillsdotnet GitHub: https://github.com/PederHP/skillsdotnet Category: Skills & Skill Registries Stars: 15 C# / .NET implementation of agentskills.io with MCP integration SkillsDotNet is a C#/.NET implementation of the agentskills.io standard designed to integrate agent skills into the Model Context Protocol (MCP). It uses a skill:// URI convention to implement progressive disclosure, allowing clients to discover lightweight skill metadata before loading full documentation or supporting files. The library provides seamless integration with Microsoft.Extensions.AI and supports automatic discovery of skills from various agent directories like Claude, Cursor, and Copilot. Highlights: - Implements progressive disclosure via SKILL.md files - Integrates with Microsoft.Extensions.AI for tool-based skill loading - Supports automatic registration of common agent skill directories --- ## jyje/hermes-agent-helm URL: https://hermesatlas.com/projects/jyje/hermes-agent-helm GitHub: https://github.com/jyje/hermes-agent-helm Category: Deployment & Infra Stars: 15 👩🏻‍💻 Hermes Agent on Kubernetes - sign in with Codex/Copilot, run agent teams, stay lightweight. jyje/hermes-agent-helm provides a Helm chart for running Hermes Agent on Kubernetes. It supports provider configuration through values, Discord or Telegram gateway connections, and optional Codex or GitHub Copilot device login with credentials persisted across restarts. The chart can also enable Hermes’s web dashboard and supports grouping multiple instances into a Hermes Team. Highlights: - Install from OCI registry or published Helm repository. - Includes provider-specific values examples. - CI installs the chart on an ephemeral kind cluster. --- ## nativ3ai/hermes-payguard URL: https://hermesatlas.com/projects/nativ3ai/hermes-payguard GitHub: https://github.com/nativ3ai/hermes-payguard Category: Plugins & Extensions Stars: 14 Safe-by-design USDC and x402 payment plugin for Hermes Agent Hermes PayGuard is a security-focused plugin that enables Hermes Agents to handle USDC and x402 payments through a gated execution model. It separates payment preparation from execution by requiring an out-of-band human approval stamp for transfers exceeding user-defined policy limits. The system supports Circle developer-controlled wallets, cross-chain CCTP transfers, and automated x402 micropayments for paid HTTP fetches. This architecture ensures that while agents can stage financial intents, they cannot unilaterally move significant funds without explicit operator consent. Highlights: - Enforces human-in-the-loop approval for high-value USDC transfers - Supports Circle CCTP for cross-chain USDC routing and execution - Automates x402 micropayments below configurable policy thresholds --- ## Sahil-SS9/llm-judge-jury-executioner URL: https://hermesatlas.com/projects/Sahil-SS9/llm-judge-jury-executioner GitHub: https://github.com/Sahil-SS9/llm-judge-jury-executioner Category: Multi-Agent & Orchestration Stars: 12 Multi-LLM deliberation council — Judge, Jury, Executioner pattern. Dynamic agent composition, cross-examination, cascade-breaking and minority reports. Research-backed synthesis of 5 community approaches and academic findings. A standalone skill and CLI that runs questions through multiple independent models using six protocols, including voting, synthesis, critique, red-team review, and full deliberation. It can produce Markdown, JSON, HTML, and transcript outputs, with configurable provider routes and bounded workspace context scanning. Highlights: - Six protocols with fail-closed configuration validation - Outputs verdicts, reports, and phase transcripts - Supports OpenAI-compatible provider APIs --- ## stepanov1975/hermes-local-knowledge URL: https://hermesatlas.com/projects/stepanov1975/hermes-local-knowledge GitHub: https://github.com/stepanov1975/hermes-local-knowledge Category: Memory & Context Stars: 11 Reusable Hermes Agent plugin for local capability indexing and routing Hermes Local Knowledge is a reusable Hermes Agent plugin that routes local questions to likely artifacts, such as skills, documents, scripts, runbooks, cron jobs, MCP servers, and generated tool-routing notes. It provides tools to search, fetch, and traverse artifacts, and its search results are routing hints; the agent should read the selected source before acting. Highlights: - Registers five tools for search, retrieval, traversal, feedback, and usage reports. - Indexes configured local sources and selected Hermes runtime sources. - Registers pre_llm_call, on_session_end, and on_session_finalize hooks. --- ## Diabloluo/hermes-hud URL: https://hermesatlas.com/projects/Diabloluo/hermes-hud GitHub: https://github.com/Diabloluo/hermes-hud Category: Skills & Skill Registries Stars: 11 Local real-time observability dashboard for Hermes Agent: timeline, health, token/cost, sessions, skills, cron, channels, errors & incidents — local-first, read-only, zero outbound telemetry. Hermes HUD is a local-first, read-only monitoring plugin for the Hermes Agent dashboard that provides real-time observability of system health, token usage, and session activity. It operates as a user-level extension using a shared snapshot cache and WebSocket events to display metrics without outbound telemetry. Highlights: - Provides real-time tracking of token costs, session history, and skill analytics. - Enforces strict read-only data access with local log desensitization. - Supports optional incident alerting via Telegram and Feishu. --- ## MukundaKatta/hermes-agentmemory URL: https://hermesatlas.com/projects/MukundaKatta/hermes-agentmemory GitHub: https://github.com/MukundaKatta/hermes-agentmemory Category: Memory & Context Stars: 10 Pull-model episodic memory plugin for Hermes Agent with real deletion (no persistent summaries that haunt future recall) and a trace.jsonl audit log of every memory operation. Community fix for issue #6715. MIT. This is a standalone memory plugin for Hermes Agent built on agentmemory. It uses a pull-model for episodic memory that performs synchronous writes and immediate deletions without leaving derived summaries behind. Highlights: - Provides an audit trace of prefetch operations via trace.jsonl - Supports real, immediate event deletion - Uses an on-demand summarizer --- ## freehul/progressive-skill URL: https://hermesatlas.com/projects/freehul/progressive-skill GitHub: https://github.com/freehul/progressive-skill Category: Guides & Docs Stars: 10 Smart skill index compaction for Hermes Agent — progressive disclosure with budget control and usage-frequency learning. Cuts skills index ~70% tokens (issue #22620). Progressive Skill reduces the size of an agent’s skills index by demoting selected categories to compact count lines and applying a configurable character budget. It uses toolset mappings and recency-weighted skill usage to decide what remains fully visible; the README says the repository is no longer actively updated and is retained as a design reference. Highlights: - Includes a Hermes plugin and an agent-agnostic Python decision core. - Demoted skills remain discoverable through skills_list. - Usage scores decay based on recency. --- ## conorbronsdon/agent-skills URL: https://hermesatlas.com/projects/conorbronsdon/agent-skills GitHub: https://github.com/conorbronsdon/agent-skills Category: Skills & Skill Registries Stars: 10 Production-tested agent skills for Claude Code, Codex, Cursor, and OpenCode — session management, multi-session reconciliation, worktree recovery, PR review, and skill scaffolding. The proportionate-r agent-skills is a collection of markdown files that teach coding agents specific workflows. It includes skills for session management, code review, state reconciliation, worktree recovery, and skill creation, with installation instructions for Claude Code and other agents. The project is in maintenance mode: it is stable, receives security fixes, and still welcomes issues and pull requests. Highlights: - Skills are installed by copying a directory or using the bundled installer. - Includes workflows for code review and session management. - Skills are plain markdown files. --- ## hermes-labs-ai/hermes-blind URL: https://hermesatlas.com/projects/hermes-labs-ai/hermes-blind GitHub: https://github.com/hermes-labs-ai/hermes-blind Category: Memory & Context Stars: 10 Recovers the original goal of a long Claude Code or Codex session from its first user turn, so you can restate it before continuing — plus a prompt wrapper that adds evidence and hedging constraints t Hermes Blind deterministically extracts the first real user turn from supported local Claude Code or Codex session transcripts and generates an inspectable Markdown recovery anchor. It also provides an evidence-bound prompt wrapper for evaluation workflows and integration options for Claude Code, Codex CLI, Gemini CLI, and Hermes Agent hooks. Highlights: - Offers goals, first-sentence, and full extraction modes. - Skips tool output and other non-user-turn records. - Does not use a summarizing model or external service. --- ## Sahil-SS9/hermes-walkie-talkie URL: https://hermesatlas.com/projects/Sahil-SS9/hermes-walkie-talkie GitHub: https://github.com/Sahil-SS9/hermes-walkie-talkie Category: Integrations & Bridges Stars: 10 Secure same-machine peer messaging for independent Hermes Agent sessions. Live session discovery, direct messages with delivery receipts, named groups and bounded broadcasts, and structured requests with status updates and idempotency — over Unix sockets or Windows named pipes, with no central daemon and no network exposure. Hermes Walkie Talkie is a standalone plugin that lets independent Hermes sessions on the same computer discover one another and coordinate through messages, groups, broadcasts, and structured requests. It uses Unix-domain sockets on Linux and macOS, and Windows named pipes with SID-bound access controls; it does not connect machines over a network or use a central daemon. Highlights: - Direct messages include delivery receipts. - Supports named groups and bounded broadcasts. - Includes Hermes tools, slash commands, and an optional Desktop panel. --- ## basilisk-labs/agentplane-hermes-plugin URL: https://hermesatlas.com/projects/basilisk-labs/agentplane-hermes-plugin GitHub: https://github.com/basilisk-labs/agentplane-hermes-plugin Category: Plugins & Extensions Stars: 9 Hermes plugin for spawning AgentPlane as an external Kanban worker lane. This plugin acts as a transport adapter to bridge AgentPlane with Hermes as a native worker-lane. It manages the execution of AgentPlane tasks while Hermes maintains ownership of Kanban task state and LLM episodes. Highlights: - Implements a native Hermes command group for AgentPlane tasks. - Provides a conversational bridge for task approvals within Hermes. - Requires AgentPlane version 0.7.6 or newer. --- ## piprail/piprail URL: https://hermesatlas.com/projects/piprail/piprail GitHub: https://github.com/piprail/piprail Category: Memory & Context Stars: 9 x402 (HTTP 402 Payment Required) SDK + MCP server: let any API charge for itself and any AI agent pay for itself, USDC & stablecoins across EVM, Solana & 8 more chain families, in a couple of lines. B PipRail is an implementation of the x402 "402 Payment Required" standard designed for agent-to-merchant payments. It provides an SDK and MCP server to enable direct wallet-to-wallet transactions across EVM, Solana, TON, Tron, NEAR, Sui, Aptos, Algorand, Stellar, and the XRP Ledger. Highlights: - Provides a TypeScript SDK for x402 payments - Includes an MCP server for budget-bound agent wallets - Operates without a backend, database, or API keys --- ## conorbronsdon/demo-gif-skill URL: https://hermesatlas.com/projects/conorbronsdon/demo-gif-skill GitHub: https://github.com/conorbronsdon/demo-gif-skill Category: Skills & Skill Registries Stars: 9 Claude Code skill: add a reproducible demo GIF to any repo's README (vhs, Playwright, ffmpeg, gifsicle) This project is a skill for Claude Code and agentskills.io-compatible agents that automates the creation of reproducible demo GIFs for repositories. It generates recording scripts using vhs for terminal interfaces or Playwright for web applications, then renders, optimizes, and embeds the resulting GIF into the README. Highlights: - Generates reproducible vhs .tape or Playwright recording scripts. - Optimizes GIF files to target sizes under 8 MB. - Supports terminal CLIs, TUIs, web apps, and libraries. --- ## hermes-labs-ai/hermeneutic URL: https://hermesatlas.com/projects/hermes-labs-ai/hermeneutic GitHub: https://github.com/hermes-labs-ai/hermeneutic Category: Plugins & Extensions Stars: 9 Turn corrections from AI agent logs into guidance for similar tasks. Local memory with semantic retrieval, prompt-context hooks, and response checks. Hermeneutic derives reviewable lesson candidates from agent corrections and original instructions, preserving the correction verbatim with provenance. After a person confirms a candidate, a host can retrieve it for a later task; the agent is expected to check its source and applicability against the current instruction. It also supports mining logs from Codex, Claude Code, and OpenAI message files. Highlights: - Candidates require confirmation before contributing context. - Lessons can be inspected, scoped, and revoked. - Matching uses conservative lexical overlap by default. --- ## Sahil-SS9/MrHermagi-tutorbot URL: https://hermesatlas.com/projects/Sahil-SS9/MrHermagi-tutorbot GitHub: https://github.com/Sahil-SS9/MrHermagi-tutorbot Category: Domain Applications Stars: 8 Discord AI tutor bot built on Hermes Agent profiles, cron jobs, forum delivery, HTML lessons, and TTS audio. MrHermagi-tutorbot is a Discord AI tutor bot that delivers daily lessons to a forum channel at 07:00 UK, with each week getting one thread and lessons posted as replies. Lessons come as a scannable Discord summary, a dark-mode HTML lesson, and TTS audio, with curriculum defined in a YAML file that can be swapped to change subjects. It runs on Hermes Agent profiles with a cron job and requires a Discord bot with Send Messages, Create Threads, and Attach Files permissions. Highlights: - Daily lessons delivered to a Discord forum at 07:00 UK - Curriculum defined in YAML; swap subjects without infrastructure changes - Includes HTML lessons, TTS audio, and a Q&A channel --- ## yonro/hermes-xmemo-plugin URL: https://hermesatlas.com/projects/yonro/hermes-xmemo-plugin GitHub: https://github.com/yonro/hermes-xmemo-plugin Category: Memory & Context Stars: 8 XMemo memory provider for Hermes Agent — durable cross-session AI memory with semantic search hermes-xmemo is a native XMemo memory provider for Hermes Agent. It supports pre-turn context recall, explicit memory tools, mirroring Hermes built-in memory writes to XMemo, and session-end snapshots. Highlights: - Runs inside Hermes and communicates with XMemo over HTTPS. - Provides ranked, bounded context recall before a turn. - Includes a local SQLite reliability layer. --- ## observeco/observeco URL: https://hermesatlas.com/projects/observeco/observeco GitHub: https://github.com/observeco/observeco Category: Developer Tools Stars: 8 Self-healing observability for AI agents. Discover, monitor, and auto-recover multi-agent systems — without a cloud dependency. ObserveCo is an open-source observability tool for monitoring and benchmarking AI agents. It provides a dashboard to track token usage, costs, and task success rates through passive traffic analysis and active probing. Highlights: - Native Hermes plugin exports real-time telemetry from agent conversations. - Two-mode monitoring includes zero-token passive analysis and scheduled active probing. - Config-aware baselines detect performance drift relative to local file changes. --- ## IVRZ-da/agentiker-code-intel URL: https://hermesatlas.com/projects/IVRZ-da/agentiker-code-intel GitHub: https://github.com/IVRZ-da/agentiker-code-intel Category: Plugins & Extensions Stars: 7 70 AST-aware code intelligence tools for Hermes Agent — tree-sitter + ast-grep + LSP bridge for Python, TypeScript, Go, Rust, and 5 more languages agentiker-code-intel is a Hermes plugin providing AST-aware code intelligence using tree-sitter, ast-grep, and LSP. It offers 70 tools for tasks such as symbol extraction, structural search, and impact analysis across supported languages. Highlights: - Supports C, C++, Go, Java, JavaScript, Python, Rust, TSX, and TypeScript - Uses a SQLite-persistent import graph for knowledge queries - Provides LSP-powered definition, references, and diagnostics --- ## conorbronsdon/agent-skill-builder URL: https://hermesatlas.com/projects/conorbronsdon/agent-skill-builder GitHub: https://github.com/conorbronsdon/agent-skill-builder Category: Skills & Skill Registries Stars: 7 A skill that builds agent skills — and doesn't rot. Spec-current frontmatter plus a validator that fails on drift. agent-skill-builder is a tool for generating and validating Claude Code and portable Agent Skills using plain-language descriptions. It includes a runtime-aware validator that detects structural drift, unsafe commands, and credential-shaped strings while enforcing specific character limits for each profile. Highlights: - Generates Claude Code extensions and portable Agent Skills core files. - Validates skills against runtime-specific profiles with CI-friendly exit codes. - Monitors official frontmatter specifications weekly to detect field drift. --- ## Senpi-ai/senpi-plugin URL: https://hermesatlas.com/projects/Senpi-ai/senpi-plugin GitHub: https://github.com/Senpi-ai/senpi-plugin Category: Domain Applications Stars: 7 Senpi — AI Quant. One plugin for Claude Code, Claude, ChatGPT, Codex, Cursor, Grok Bot and Grok Build: connect your AI assistant to your own Senpi agent for Hyperliquid. Senpi is a plugin that connects supported AI assistants to a user's Senpi agent for Hyperliquid research and strategy workflows. It forwards messages to the Senpi server and returns replies; proposed trades and fund movements require user approval. Highlights: - Offers market signals, trader research, and portfolio review. - Runs nothing on the user's machine. - Uses OAuth 2.0 over HTTPS. --- ## gizdusum/hermes-blockchain-oracle URL: https://hermesatlas.com/projects/gizdusum/hermes-blockchain-oracle GitHub: https://github.com/gizdusum/hermes-blockchain-oracle Category: Integrations & Bridges Stars: 6 Solana blockchain intelligence MCP server — wallets, whales, tokens, NFTs, network health Hermes Blockchain Oracle is a Model Context Protocol (MCP) server that provides Hermes Agent with real-time access to the Solana blockchain. It functions as a bridge between natural language queries and on-chain data by exposing specialized tools for wallet, token, and transaction analysis. The server enables users to monitor network health, track whale movements, and manage NFT portfolios through conversational interactions. By integrating directly with Solana RPC nodes, it eliminates the need for manual block explorer searches. Highlights: - Provides real-time Solana wallet balances and token portfolio tracking - Detects large-scale whale transfers with configurable movement thresholds - Retrieves NFT metadata, collection details, and floor price information --- ## hlothaire/hermes-trace URL: https://hermesatlas.com/projects/hlothaire/hermes-trace GitHub: https://github.com/hlothaire/hermes-trace Category: Plugins & Extensions Stars: 6 A Hermes Agent plugin that builds execution trace graphs using agent lifecycle hooks. Hermes Trace is a plugin that provides visibility into agent execution by building structured trace graphs of session activity. It utilizes 18 lifecycle hooks to automatically capture LLM calls, tool usage, subagent spawns, and approval requests. Users can analyze these traces via a dedicated CLI or an in-session slash command to identify bottlenecks and track token usage. The system ensures reliability by wrapping all hooks in error-handling blocks and requires no runtime dependencies beyond the Python standard library. Highlights: - Captures 18 lifecycle hooks for comprehensive event tracing - Exports traces as JSON, Mermaid diagrams, and text trees - Includes ASCII Gantt timelines for analyzing span concurrency --- ## MnrGreg/hermes-venice-web URL: https://hermesatlas.com/projects/MnrGreg/hermes-venice-web GitHub: https://github.com/MnrGreg/hermes-venice-web Category: Plugins & Extensions Stars: 6 Hermes plugin that uses Venice.AI web_search and web_scrape tools This plugin registers Venice AI's /augment endpoints as native web_search and web_extract backends within Hermes. It allows agents to use Venice for web searching and scraping through standard Hermes web tool infrastructure. Highlights: - Integrates Venice AI /augment/search and /augment/scrape endpoints - Supports Brave or Google as search providers - Compatible with any LLM provider --- ## aidevelopers2/remoteopenclaw-mcp URL: https://hermesatlas.com/projects/aidevelopers2/remoteopenclaw-mcp GitHub: https://github.com/aidevelopers2/remoteopenclaw-mcp Category: Skills & Skill Registries Stars: 6 Search 13,870+ MCP servers, 4,384+ agent skills, and plugins from your terminal or AI agent. CLI + MCP server for remoteopenclaw.com Remote OpenClaw MCP Server provides a command-line and agent-native interface for searching a directory of over 13,000 MCP servers and 4,000 agent skills. It functions as a thin TypeScript wrapper around the Remote OpenClaw public search API, allowing agents to retrieve tool metadata and installation commands without a browser. This integration enables agents like Hermes and Claude Code to autonomously discover and suggest relevant plugins for tasks such as database management or web scraping. The server requires no API key and integrates directly into standard MCP client configurations. Highlights: - Searches over 13,870 MCP servers and 4,384 agent skills - Provides direct installation commands for discovered tools and plugins - Integrates with MCP-compatible clients like Hermes, Cursor, and Claude Code --- ## Carlo1911/skill-evolution URL: https://hermesatlas.com/projects/Carlo1911/skill-evolution GitHub: https://github.com/Carlo1911/skill-evolution Category: Skills & Skill Registries Stars: 6 Self-improvement feedback loop for AI agent skills — analyzes past sessions, drafts structured improvement proposals, and gates auto-apply behind an evaluation framework. Host-agnostic (Hermes, Claude Skill Evolution analyzes past agent sessions against installed skills and creates structured proposal files for review. Approved proposals can be applied through an evaluation gate; adapters are provided for Hermes and Claude Code. Highlights: - Fetches sessions and indexes installed skills. - Proposals are review-only by default. - Evaluation gate supports deterministic, LLM-judge, and regression evaluators. --- ## futurebrowser/hermes-exabase-plugin URL: https://hermesatlas.com/projects/futurebrowser/hermes-exabase-plugin GitHub: https://github.com/futurebrowser/hermes-exabase-plugin Category: Memory & Context Stars: 5 Exabase memory plugin for Hermes Agent. This plugin integrates the Exabase M-1 memory engine into Hermes Agent to provide persistent, long-term context for AI interactions. It functions by storing conversation turns and inferred memories in a self-organizing knowledge graph that resolves contradictions and evolves over time. Users can configure retrieval precision, enable query expansion, and utilize result reranking to fine-tune how the agent accesses stored facts and preferences. The integration includes dedicated tools for manual memory storage and searching, while also automatically processing conversation history in the background. Highlights: - Integrates Exabase M-1 for self-organizing long-term agent memory. - Provides tools for searching and manually storing specific memories. - Supports configurable query expansion and result reranking for retrieval. --- ## sourcevault-ai/sourcevault-code-tools URL: https://hermesatlas.com/projects/sourcevault-ai/sourcevault-code-tools GitHub: https://github.com/sourcevault-ai/sourcevault-code-tools Category: Memory & Context Stars: 5 Hermes Agent plugin — private local code memory for your repos (semantic search, file reads, grounded Q&A) sourcevault-code-tools is a Hermes Agent plugin for searching code, reading exact files, and answering repository questions with file-and-line citations. It connects to a separate SourceVault backend and is described as running on the user’s machine over localhost without source code leaving it. Highlights: - Provides slash commands for search, file reads, context, and Q&A. - Supports Hermes CLI, Telegram, and Hermes Desktop. - Includes repo sync and indexed git-history search commands. --- ## IVRZ-da/agentiker-plan-follow URL: https://hermesatlas.com/projects/IVRZ-da/agentiker-plan-follow GitHub: https://github.com/IVRZ-da/agentiker-plan-follow Category: Plugins & Extensions Stars: 5 Structured plan creation & task enforcement for Hermes Agent — review gates, parallel groups, auto-verify, git integration, 12 templates plan_follow is a Hermes plugin for structured plan creation and task enforcement. It provides tools for managing task dependencies, parallel execution groups, review gates, and git integration. Highlights: - Supports 12 templates for plan creation - Includes 6 review profiles for task validation - Provides git integration for branches, commits, and PRs --- ## visorcraft/MongrelDB-Hermes URL: https://hermesatlas.com/projects/visorcraft/MongrelDB-Hermes GitHub: https://github.com/visorcraft/MongrelDB-Hermes Category: Memory & Context Stars: 5 AI-native long-term memory for Hermes Agent with AES-256-GCM encryption at rest, dense HNSW ANN, sparse and exact-text recall, metadata/range filters, and MinHash dedup, backed by an embedded or multi MongrelDB-Hermes is a hybrid long-term memory plugin for the Hermes Agent that uses multiple index types for retrieval. It supports dense ANN, sparse retrieval, exact text, and metadata filtering with built-in MinHash deduplication. Highlights: - Supports AES-256-GCM encryption at rest by default - Offers native Rust FFI or HTTP daemon execution modes - Includes HNSW ANN, sparse, and FM-index retrieval --- ## Fruxano/fruvisi URL: https://hermesatlas.com/projects/Fruxano/fruvisi GitHub: https://github.com/Fruxano/fruvisi Category: Plugins & Extensions Stars: 5 Visual organization dashboard plugin for Hermes Agent — org chart with areas & groups, one-click team lineups (functional presets), per-agent OpenRouter fallback, kanban integration and chat control. FruVisi is a dashboard plugin for Hermes Agent that provides an interactive 2D organizational chart for managing agent structures. It enables functional presets for team lineups, per-agent OpenRouter fallbacks, and kanban task integration via the native Hermes API. Highlights: - Interactive 2D org chart using React Flow - One-click functional presets for team lineups - Per-agent OpenRouter fallback configuration --- ## chillerno1/hermes-yt-plugin URL: https://hermesatlas.com/projects/chillerno1/hermes-yt-plugin GitHub: https://github.com/chillerno1/hermes-yt-plugin Category: Plugins & Extensions Stars: 5 A floating YouTube player plugin for Hermes Desktop This plugin provides a compact YouTube player for the Hermes Desktop client that functions in floating or docked modes. It uses an isolated Electron webview to play watch pages, playlists, Shorts, Live, and embed links without requiring an API key. Highlights: - Supports floating or docked pane modes - Saves favourites and up to 50 recent videos - Uses an isolated webview session --- ## handnewb/hermes-voice URL: https://hermesatlas.com/projects/handnewb/hermes-voice GitHub: https://github.com/handnewb/hermes-voice Category: Developer Tools Stars: 5 Voice-enabled personal assistant for Hermes Agent. Open mic with wake word, fully local — no API keys, no accounts, 35 languages. Hermes-voice is a voice-enabled personal assistant designed for Hermes Agent. It operates entirely locally using speech recognition, voice activity detection, wake word detection, and speech synthesis. Highlights: - Supports 35 languages via Piper and 9 via Kokoro. - Features adaptive turn-taking and barge-in capabilities. - Runs offline with no API keys or accounts required. --- ## kevinmarmstrong/hermes-claude-code-rc URL: https://hermesatlas.com/projects/kevinmarmstrong/hermes-claude-code-rc GitHub: https://github.com/kevinmarmstrong/hermes-claude-code-rc Category: Integrations & Bridges Stars: 4 Hermes Agent plugin for remote controlling Claude Code sessions via Telegram This Hermes Agent plugin enables remote management of Claude Code sessions through Telegram or other Hermes-connected platforms. It bridges the gap between local filesystem access and mobile convenience by starting a Claude Remote Control session on a host machine via slash commands. The plugin monitors subprocess output to capture session URLs, allowing users to control their local environment from the Claude mobile app without needing a terminal. It also supports headless command execution and shell access with built-in safety filters for dangerous operations. Highlights: - Starts Claude Code remote sessions via Telegram slash commands - Provides full local filesystem and tool access from mobile devices - Executes headless commands and shell operations with safety filtering --- ## penfieldlabs/hermes-penfield URL: https://hermesatlas.com/projects/penfieldlabs/hermes-penfield GitHub: https://github.com/penfieldlabs/hermes-penfield Category: Memory & Context Stars: 4 🧠 Penfield memory providers for Hermes agent hermes-penfield is a persistent memory provider that enables Hermes Agent to maintain memory across different sessions and agents. It connects the agent to the Penfield memory API using a stdlib-only HTTP implementation with OAuth and API-key authentication. The provider utilizes hybrid search and a knowledge graph with 24 relationship types to manage memories and artifacts. It also automatically saves checkpoints of relevant memories when context compression occurs. Highlights: - 17 tools for memory management and knowledge graph traversal - Hybrid search combining BM25, vector, and graph methods - Automatic context checkpointing during message compression --- ## IVRZ-da/agentiker-scout URL: https://hermesatlas.com/projects/IVRZ-da/agentiker-scout GitHub: https://github.com/IVRZ-da/agentiker-scout Category: Plugins & Extensions Stars: 4 Unified analysis, bug-hunt & web-research plugin for Hermes Agent — 43 tools across code analysis, vulnerability scanning, and autonomous research agentiker-scout is a Hermes plugin providing tools for code and architecture analysis, vulnerability scanning, and autonomous web research. It utilizes a shared pattern pipeline to allow findings from analysis scans to inform automated bug-hunt scans. Highlights: - Includes 56 tools across three functional domains - Supports automated pattern-based vulnerability scanning - Provides autonomous web research with lifecycle management --- ## chenwei791129/hermes-usage-hook URL: https://hermesatlas.com/projects/chenwei791129/hermes-usage-hook GitHub: https://github.com/chenwei791129/hermes-usage-hook Category: Plugins & Extensions Stars: 4 Hermes Agent footer hook: append your AI provider's rate-limit usage (Codex, MiniMax, …) under each reply. Hermes Usage Hook appends a line showing rate-limit usage to each reply when it recognizes a supported provider from the reply’s model name. It supports Codex and MiniMax, skips the footer if fetching usage fails, and requires the relevant provider credentials. Highlights: - Shows usage for available 5-hour and weekly windows. - Supports Codex and MiniMax model names. - Failed usage fetches do not break replies. --- ## 33hodl/hermes-startup URL: https://hermesatlas.com/projects/33hodl/hermes-startup GitHub: https://github.com/33hodl/hermes-startup Category: Developer Tools Stars: 4 Make your first genuine dollar online using Hermes Agent. Hermes Startup is a local-first skill for Hermes Agent designed to help users identify and test business ideas. The tool uses a series of focused questions to generate evidence-labeled ideas and prepares reversible tests for chosen problems. Highlights: - Operates as a deterministic zero-network local runtime by default. - Requires explicit approval for all consequential actions and external writes. - Includes contracts for opportunities, offer-previews, and exact-approvals. --- ## superagnt/leverage URL: https://hermesatlas.com/projects/superagnt/leverage GitHub: https://github.com/superagnt/leverage Category: Skills & Skill Registries Stars: 4 Agents are the newest form of leverage. Skills + blueprints that give yours something real to work with: live social data, people + company enrichment, a workspace Postgres, schedules, shareable dashb Leverage is a collection of agent skills for accessing social and web data, enriching people and companies, and using a Postgres database, task agents, schedules, and dashboards. It also includes packaged skills for complete jobs and can be installed with clients that read SKILL.md. Highlights: - Includes skills for social platforms and web data. - Offers packaged skills for complete jobs. - Supports installation through SKILL.md-compatible clients. --- ## BORT-AGENTS/hermes-bort URL: https://hermesatlas.com/projects/BORT-AGENTS/hermes-bort GitHub: https://github.com/BORT-AGENTS/hermes-bort Category: Integrations & Bridges Stars: 3 No description hermes-bort is a plugin for Hermes Agent that enables interaction with BORT (BAP-578) agent NFTs on the BSC mainnet. It allows Hermes processes to read on-chain agent states, execute actions via operator-signed writes, and manage portable session memory anchored to IPFS. The plugin integrates with the hermes-agent-self-evolution optimizer to commit verifiable on-chain learning records and evolved skills directly to an agent's knowledge registry. Highlights: - Reads full agent state, IPFS identity, and knowledge registries - Executes on-chain actions via VaultPermissionManagerV2 with local policy gating - Anchors local session memory to IPFS and KnowledgeRegistryV2 --- ## DanielLi202/hermes-tag URL: https://hermesatlas.com/projects/DanielLi202/hermes-tag GitHub: https://github.com/DanielLi202/hermes-tag Category: Integrations & Bridges Stars: 3 Post images, add notes, let the thread run, then @ it — Hermes Tag pulls the few messages that matter (originals + your notes + relevant replies), not your last line, not your whole history. Claude-Ta Hermes Tag is a context-selection layer for Hermes on Feishu/Lark, Slack, and DingTalk. It retrieves specific images, notes, and relevant replies when @-mentioned to provide bounded evidence without processing entire chat histories. Highlights: - Provides per-chat memory isolation - Supports Feishu, Slack, and DingTalk - Uses Tier-0 short-term and Tier-1 long-term memory --- ## handnewb/lock-on-absence URL: https://hermesatlas.com/projects/handnewb/lock-on-absence GitHub: https://github.com/handnewb/lock-on-absence Category: Domain Applications Stars: 3 🔒 Auto-lock your screen when you walk away. Face recognition via LBPH, SFace, or LLM (OpenAI, Anthropic, Ollama, Hermes Agent). Privacy-first: local-first, egress gate, TrustPolicy tiers T3→T0. Lock on Absence is a Python-based tool that automatically locks a workstation when the user is no longer present. It uses webcam frames and various recognition backends to determine presence and manage workstation state. Highlights: - Supports LBPH, SFace, and LLM recognition backends. - Includes a watchdog to lock the screen if the agent fails. - Provides a FAR/FRR measurement harness and SIEM audit trail. --- ## CorsenAI/hermes-windows-runtime-skills URL: https://hermesatlas.com/projects/CorsenAI/hermes-windows-runtime-skills GitHub: https://github.com/CorsenAI/hermes-windows-runtime-skills Category: Skills & Skill Registries Stars: 3 Hermes Agent skills for deterministic path routing and non-installing Python runtime selection across Windows, Git Bash/MSYS, and WSL. This community-maintained skill pack for Hermes Agent provides deterministic path routing and Python runtime selection across Windows, Git Bash/MSYS, and WSL. It enables agents to identify execution domains and verify existing Python interpreters without installing new software or modifying project files. Highlights: - Routes file operations using environment-specific path syntax. - Selects and verifies existing project-compatible Python interpreters. - Supports native Windows, Git Bash/MSYS, and WSL environments. --- ## masterlf/hermes-ai-usage URL: https://hermesatlas.com/projects/masterlf/hermes-ai-usage GitHub: https://github.com/masterlf/hermes-ai-usage Category: Plugins & Extensions Stars: 3 Read-only provider quota and token telemetry for Hermes Agent Desktop and Web Dashboard Hermes AI Usage Monitor is a read-only extension for Hermes Agent that provides telemetry for provider quotas and local token usage. It supports the native Desktop app and Web Dashboard, displaying session history and consumption metrics without reading prompt or message content. Highlights: - Tracks official provider quotas for OpenAI Codex, Anthropic, and OpenRouter. - Displays local token counters and session history from SQLite state. - Adds zero runtime dependencies by reusing existing Hermes core components. --- ## Hiutaky/token-saver URL: https://hermesatlas.com/projects/Hiutaky/token-saver GitHub: https://github.com/Hiutaky/token-saver Category: Plugins & Extensions Stars: 3 Hermes Agent plugin: measure the money your local (free) AI saves you vs OpenRouter pricing Token Saver is a Hermes Agent plugin that calculates the hypothetical cost of local AI inference based on live OpenRouter pricing. It tracks token usage from local providers like Ollama and LM Studio to visualize simulated savings through a web dashboard, TUI widget, and slash commands. Highlights: - Calculates simulated savings using live OpenRouter pricing data. - Estimates token counts from byte length for local providers. - Operates locally using Python standard library with no external dependencies. --- ## pdalinis/incise URL: https://hermesatlas.com/projects/pdalinis/incise GitHub: https://github.com/pdalinis/incise Category: Plugins & Extensions Stars: 3 Make small AI models reliable at editing Markdown. Incise provides safe, semantic, byte-preserving edits for AI agents. Incise is a CLI and agent-tool backend for making precise, byte-preserving edits to Markdown tables, lists, sections, and YAML frontmatter. Callers specify what should change by content-based addresses, and deterministic code handles formatting, boundaries, and the smallest possible splice. It is intended for AI-maintained documentation, Obsidian vaults, Markdown knowledge bases, and local models with limited context. Highlights: - Semantic addresses select headings, rows, items, and keys by content - Minimal edits change only the targeted structural range - Ambiguous or unsafe requests fail loudly with actionable refusals --- ## roli-lpci/rule-audit URL: https://hermesatlas.com/projects/roli-lpci/rule-audit GitHub: https://github.com/roli-lpci/rule-audit Category: Plugins & Extensions Stars: 3 Static analyzer for AI system prompts: parses a prompt into normative rules and reports contradictions, coverage gaps, priority ambiguities, and absolute-rule edge cases - no LLM calls. Deterministic rule-audit statically analyzes AI system prompts and agent instructions, reporting logical contradictions, coverage gaps, priority ambiguities, meta-rule paradoxes, and absolute-rule edge cases without calling an LLM. It can run as a CLI or pre-commit hook and is available as a plugin for Claude Code, Codex, Gemini CLI, and GitHub Copilot CLI. Highlights: - Produces Markdown, JSON, or summary reports. - Pre-commit hook audits prompt files before commit. - Pure Python with no runtime dependencies. --- ## jiawood2006/hermes-skills URL: https://hermesatlas.com/projects/jiawood2006/hermes-skills GitHub: https://github.com/jiawood2006/hermes-skills Category: Skills & Skill Registries Stars: 2 Hermes Skills: 视频转文字 / AI文案去味 / 文档OCR / 电商素材工坊 (Video-to-text, AI text de-humanizer, OCR, E-commerce Material Studio) Hermes Skills is a collection of nine open-source tools designed for Chinese-language agent tasks such as video transcription, document OCR, and text refinement. The project provides scripts for processing Douyin links, generating e-commerce product scenes, and managing long-form writing memory. Highlights: - Transcribes Douyin videos to structured Markdown and SRT subtitles. - Removes common Chinese AI writing patterns using a rule-based engine. - Extracts structured data from PDFs and images using macOS Vision. --- ## webmilmind1/hermes-bounty-board URL: https://hermesatlas.com/projects/webmilmind1/hermes-bounty-board GitHub: https://github.com/webmilmind1/hermes-bounty-board Category: Skills & Skill Registries Stars: 2 Hermes Agent plugin: earn USDC answering real support bounties, or run your own bounty board, over x402. No account, no API key. A human approves the winning answer and the wallet is paid 85% automati hermes-bounty-board is a Hermes Agent plugin for answering customer support bounties or running a bounty board. It uses x402 over HTTP; a business human approves the winning answer, and the submitting wallet receives 85% of the reward automatically. This Python plugin pays on Base. Highlights: - Lists open bounties and provides public wallet earnings records. - Lets agents buy ticket context and submit answers for review. - Board creation returns a URL, API key, and USDC deposit addresses. --- ## conorbronsdon/agent-memory-kit URL: https://hermesatlas.com/projects/conorbronsdon/agent-memory-kit GitHub: https://github.com/conorbronsdon/agent-memory-kit Category: Memory & Context Stars: 2 The curation pass for agent memory: a thin, file-based loop that finds rot and contradictions and proposes evidence-cited diffs you review. Markdown in, JSON out, no database. The memory-hygiene leg o agent-memory-kit is a file-based curation loop designed to identify contradictions and outdated information within an agent's memory store. It uses a set of five markdown-based commands to capture, recall, and audit memory through evidence-cited diffs without requiring a database or vector store. Highlights: - Operates using plain markdown files and JSON diffs. - Includes 'rot' and 'lint' curators to find stale or conflicting facts. - Uses a local git repository to track and revert memory changes. --- ## Bandwidth/smartnumbers-hermes URL: https://hermesatlas.com/projects/Bandwidth/smartnumbers-hermes GitHub: https://github.com/Bandwidth/smartnumbers-hermes Category: Plugins & Extensions Stars: 2 Hermes plugin for the smartnumbers service Hermes Smartnumbers receives and archives Smartnumbers conversation transcripts, with tools for searching archived turns and managing post-call reviews. When enabled, it can queue one-shot Hermes cron jobs for transcript reviews and user-configured callbacks. Highlights: - Archives transcripts and supports searching transcript turns. - Queues post-call reviews as one-shot Hermes cron jobs. - Supports configurable, independent post-call callbacks. --- ## taskawayfr/hermes-agent-fr URL: https://hermesatlas.com/projects/taskawayfr/hermes-agent-fr GitHub: https://github.com/taskawayfr/hermes-agent-fr Category: Guides & Docs Stars: 2 Guide pratique de Hermes Agent en français : installation, Telegram, profils, sécurité, tâches programmées, migration depuis OpenClaw Guide pratique en français pour installer et configurer Hermes Agent, le connecter à Telegram, gérer les profils et la sécurité, et programmer des tâches. Il comprend aussi des chapitres sur le dépannage, les coûts, l’hébergement, la migration depuis OpenClaw et des cas d’usage pour petites entreprises. Highlights: - Fournit des exemples prêts à copier et testés. - Vérifie les commandes, exemples et liens automatiquement. - Publié sous licence Creative Commons Attribution 4.0. --- ## nicolasestrem/hermes-model-switcher URL: https://hermesatlas.com/projects/nicolasestrem/hermes-model-switcher GitHub: https://github.com/nicolasestrem/hermes-model-switcher Category: Workspaces & GUIs Stars: 2 One-click cross-profile model switching plugin for the Hermes Agent Web Dashboard Hermes Model Switcher is a community plugin for the Hermes Web Dashboard that displays supported model routes across profiles in a searchable, filterable table. Users can preview model changes, apply them, save choices as presets, review per-profile results, and use revision-guarded Undo. Highlights: - Shows configured routes across profiles in one matrix. - Previews changes before applying them. - Includes named presets and guarded Undo. --- ## f-o-x11/deed-page-skill URL: https://hermesatlas.com/projects/f-o-x11/deed-page-skill GitHub: https://github.com/f-o-x11/deed-page-skill Category: Skills & Skill Registries Stars: 2 Agent skill: publish files to a permanent deed.page URL with one curl request. No account. This repository contains an agent skill that publishes a file or folder to a permanent deed.page URL with one curl request, and documents deed.page’s hosted remote MCP server. The MCP server can publish and manage sites, including updating, versioning, password-protecting, and deleting them; the skill and server are described as compatible with several agent clients. Highlights: - Publishes files or folders to permanent deed.page URLs. - Documents a hosted remote MCP server at deed.page/mcp. - Includes agent plugin manifests and installation instructions. --- ## Webly-AI/webly-plugin URL: https://hermesatlas.com/projects/Webly-AI/webly-plugin GitHub: https://github.com/Webly-AI/webly-plugin Category: Plugins & Extensions Stars: 2 Webly skill and Claude Code plugin: let AI agents publish a folder or HTML file to a live URL in seconds, then claim, edit and publish it over MCP. Webly provides an agent skill and plugins for publishing a folder or website to a live Webly URL without an account. Users can claim a site by signing in, then work with it through Webly’s MCP server, including editing and publishing. Highlights: - Installs for Claude Code, Cursor, Gemini CLI, and other agents. - Unclaimed sites are live for 24 hours and claimable for 7 days. - MCP access supports site editing, publishing, and rollback. --- ## marospekarik/paperclip-hermes-file-access-manager URL: https://hermesatlas.com/projects/marospekarik/paperclip-hermes-file-access-manager GitHub: https://github.com/marospekarik/paperclip-hermes-file-access-manager Category: Plugins & Extensions Stars: 2 Kernel-enforced filesystem sandboxing for Hermes Agent profiles. A Paperclip plugin that turns per-path permission rules into Docker bind mounts. File Access Manager is a Paperclip plugin that sets per-path Read/Write, Read Only, or Denied permissions for Hermes profiles. It translates those rules into Docker bind mounts and uses Hermes’ Docker terminal backend to enforce access inside a container. The plugin provides a filesystem tree editor, previews generated mounts, and can apply changes by recreating the container and restarting the gateway. Highlights: - Denied paths are absent from the container by default. - Folder permissions inherit downward; deeper rules override. - Includes unit tests and real-Docker integration tests. --- ## kfa-ai/hermes-timetree-sync URL: https://hermesatlas.com/projects/kfa-ai/hermes-timetree-sync GitHub: https://github.com/kfa-ai/hermes-timetree-sync Category: Integrations & Bridges Stars: 1 Non-interactive TimeTree calendar bridge for Hermes Agent hermes-timetree-sync is a Python-based CLI and library that enables Hermes Agents to manage TimeTree calendar events without manual user intervention. Since TimeTree discontinued its official API, this bridge uses authenticated web endpoints and session cookies to perform non-interactive writes. It supports creating all-day events directly via HTTP requests and timed events through a Safari-backed automation path. The tool allows agents to translate natural language requests into structured calendar updates using locally stored credentials and optional label mapping policies. Highlights: - Syncs all-day and timed events using TimeTree web endpoints - Supports non-interactive batch writes for multiple calendar entries - Maps natural language terms to calendar labels via YAML policy --- ## mag3nt-com/openclaw-skill URL: https://hermesatlas.com/projects/mag3nt-com/openclaw-skill GitHub: https://github.com/mag3nt-com/openclaw-skill Category: Skills & Skill Registries Stars: 1 Openclaw Skills mag3nt-pay is an agent payment skill that enables AI agents to autonomously pay for APIs that return HTTP 402 Payment Required errors. It works by detecting payment protocols from response headers, decoding the payment challenge, and settling the transaction using USDC via Mag3nt virtual cards. The skill supports Base, Solana, and most EVM networks, allowing agents to handle micropayments and subscriptions without human intervention. It is compatible with OpenClaw, Hermes Agent, and any framework following the agentskills.io standard. Highlights: - Automates payments for HTTP 402 responses using USDC - Supports Pay Link, x402, MPP, and AP2 protocols - Compatible with OpenClaw, Hermes Agent, and agentskills.io standard --- ## AgentLineHQ/agentline-skill URL: https://hermesatlas.com/projects/AgentLineHQ/agentline-skill GitHub: https://github.com/AgentLineHQ/agentline-skill Category: Integrations & Bridges Stars: 1 No description --- ## corsur/swarm-tips URL: https://hermesatlas.com/projects/corsur/swarm-tips GitHub: https://github.com/corsur/swarm-tips Category: Plugins & Extensions Stars: 1 Swarm Tips — AI agent discovery and coordination. Smart contracts, MCP server, shared crates. Swarm Tips is an AI agent platform featuring Solana and EVM smart contracts for decentralized coordination and task marketplaces. It includes the Coordination Game for anonymous social deduction and Shillbot for AI-driven content creation tasks, supported by a Model Context Protocol (MCP) server for agent interaction. Highlights: - Supports Solana (Anchor) and EVM (Foundry) smart contract deployments. - Provides MCP server endpoints for AI agent discovery and messaging. - Implements on-chain escrow for task payments and game stakes. --- ## skillseal/skillseal URL: https://hermesatlas.com/projects/skillseal/skillseal GitHub: https://github.com/skillseal/skillseal Category: Skills & Skill Registries Stars: 1 Functional quality seal for AI agent skills. Tests every skill in an isolated Docker environment - structure, functionality and security - and certifies it actually works. SkillSeal is a trust system for AI agent skills that uses verifiable evidence and cryptographic signatures to certify them. It employs an evaluator to test skills in isolated Docker containers and a certifying authority to sign the resulting evidence. Highlights: - Tests structure, functionality, and security in isolated Docker containers - Produces cryptographically verifiable certificates using Ed25519 signatures - Provides a public API for certificate verification and skill submission --- ## scavio-ai/hermes-agent URL: https://hermesatlas.com/projects/scavio-ai/hermes-agent GitHub: https://github.com/scavio-ai/hermes-agent Category: Skills & Skill Registries Stars: 1 Scavio for Hermes Agent - structured web data across 31 platforms via the hosted MCP server, plus 5 ready-to-use workflow skills. Scavio for Hermes Agent provides structured web data from 31 platforms and an Extract endpoint via a hosted MCP server. It includes five ready-to-use skills and is compatible with clients following the Agent Skills standard. Highlights: - Exposes 191 tools via MCP server - Includes five production-grade skills - Supports Claude, Cursor, Goose, and OpenHands --- ## jiawood2006/ai-project-advisor URL: https://hermesatlas.com/projects/jiawood2006/ai-project-advisor GitHub: https://github.com/jiawood2006/ai-project-advisor Category: Domain Applications Stars: 1 工程项目 AI 顾问（AI Project Advisor）——微信对话式工程管理：记忆图谱/多群接入/规则+大模型混合/风险雷达。Construction project AI advisor: memory graph, multi-group, rule+LLM hybrid engine. AI Project Advisor is a chat-based assistant for construction projects on WeCom, DingTalk, and H5. It turns messages into project records, tracks milestones and receivables, flags risks, and generates briefings; rule-based commands handle supported tasks, with an LLM fallback for open-ended questions and summaries. Highlights: - Uses a separate SQLite database per tenant. - Includes a reversible masking layer before model requests. - Supports WeCom, DingTalk, and H5. --- ## parkyucheol-del/alphapipeline URL: https://hermesatlas.com/projects/parkyucheol-del/alphapipeline GitHub: https://github.com/parkyucheol-del/alphapipeline Category: Skills & Skill Registries Stars: 1 Quantitative Risk & Slippage Guard for AI Agents: Polymarket L2 VWAP, On-chain DEX & Cross-Venue Arbitrage (x402 Remote MCP) AlphaPipeline provides paid, per-call endpoints for token risk checks and market data, using x402 payments on Base. It also exposes a remote MCP server that clients can use to discover and call its tools; discovery is free, and two onboarding tools are permanently free. Highlights: - Checks token honeypot, tax, and liquidity risk. - Provides market data including DEX slippage and funding rates. - Offers REST endpoints and a remote MCP server. --- ## robbyczgw-cla/hermes-ui-plus URL: https://hermesatlas.com/projects/robbyczgw-cla/hermes-ui-plus GitHub: https://github.com/robbyczgw-cla/hermes-ui-plus Category: Workspaces & GUIs Stars: 1 Interactive chat client for your self-hosted Hermes Agent – approvals, live tool steps, ~50 interactive answer cards. Android · Web · macOS. Unofficial, open source. HUI+ is an unofficial mobile, web, and desktop client for a self-hosted Hermes Agent. It lets users respond to interactive answers, approve or deny commands, and follow tool steps live; it requires Hermes Agent and a locally run bridge. Highlights: - Interactive answers include checklists, choices, forms, rankings, and votes. - Command approvals and live tool-step updates. - Runs on Android, web, macOS, and Linux alpha. --- ## NickSF189/kisscode-agent URL: https://hermesatlas.com/projects/NickSF189/kisscode-agent GitHub: https://github.com/NickSF189/kisscode-agent Category: Skills & Skill Registries Stars: 1 Skill for AI agents to join KissCode (kisscode.ai): SKILL.md + HEARTBEAT.md This repository provides a skill for AI agents to join KissCode, a relationship network where AI agents and people meet. It includes installation instructions, a one-call registration example, and guidance to add HEARTBEAT.md to an agent’s routine. Highlights: - Supports agents that read SKILL.md. - Provides installation instructions for several agent environments. - The repository mirrors kisscode.ai/skill.md. --- ## wjgoarxiv/lithermes URL: https://hermesatlas.com/projects/wjgoarxiv/lithermes GitHub: https://github.com/wjgoarxiv/lithermes Category: Plugins & Extensions Stars: 1 Add one word, `lit`, to a Hermes Agent request and get a planned, tested, reviewed workflow, plus a handoff note so the next session knows where you left off. LitHermes is a plugin for Hermes Agent that starts a workflow when a request begins with `lit`. It plans the task, checks the result, and records goals, plans, and evidence on disk, with a handoff note to help a later session continue. Highlights: - Supports `lit` requests and `/lit` commands. - Records work and evidence on disk. - Provides a handoff note for the next session. --- ## silent-reader-cn/hermes-anywhere URL: https://hermesatlas.com/projects/silent-reader-cn/hermes-anywhere GitHub: https://github.com/silent-reader-cn/hermes-anywhere Category: Workspaces & GUIs Stars: 1 A Flutter client for Hermes Agent: Windows and Android are the same app — same interface, same sessions. Native desktop window; the installer bundles the WebUI backend and a Python runtime, so there i Hermes Anywhere is a Flutter and Cupertino client for Hermes Agent, with the same interface and sessions on Windows and Android. It supports streaming chat, session management, workspace tools, Kanban boards, and usage insights; the Windows installer bundles a WebUI backend and Python 3.11 runtime. Highlights: - Shared interface and sessions across Windows and Android - Streaming chat with reasoning and tool-call cards - Windows installer includes a WebUI backend and Python runtime --- ## Cyber-Yichen/hermes-xiaomi-mimo-tts URL: https://hermesatlas.com/projects/Cyber-Yichen/hermes-xiaomi-mimo-tts GitHub: https://github.com/Cyber-Yichen/hermes-xiaomi-mimo-tts Category: Plugins & Extensions Stars: 0 Xiaomi MiMo V2.5 TTS provider for Hermes Agent with native Feishu/Lark OGG/Opus voice-message delivery. This plugin integrates Xiaomi MiMo V2.5 TTS into Hermes Agent to enable high-quality voice responses. It de-codes MiMo's Chat Completions API output and uses ffmpeg to transcode audio into OGG/Opus format. This process allows for native voice-message delivery within Feishu and Lark environments. The implementation avoids external dependencies like the OpenAI SDK and ensures secure credential handling via environment variables. Highlights: - Converts MiMo TTS to OGG/Opus for Feishu voice messages - Supports standard API and Token Plan credentials - Automatic ffmpeg fallback to MP3 audio attachments --- ## Cyber-Yichen/hermes-feishu-group-context URL: https://hermesatlas.com/projects/Cyber-Yichen/hermes-feishu-group-context GitHub: https://github.com/Cyber-Yichen/hermes-feishu-group-context Category: Plugins & Extensions Stars: 0 Local Feishu/Lark group chat archiving and on-demand context for Hermes Agent. Hermes Feishu Group Context is a plugin that provides local archiving and on-demand context retrieval for Feishu/Lark group chats. It uses a local SQLite database to store messages, ensuring that model tokens are only consumed when the agent is explicitly triggered. The system automatically injects recent history during empty mentions or provides specific time-range summaries via a dedicated tool. This approach allows the agent to maintain group awareness without processing every message in real-time. Highlights: - Local SQLite storage for group chat archiving and persistence - Automatic context injection for empty mentions and relevant queries - Customizable retention periods and context window sizes per group --- ## Shine8592/china-briefing URL: https://hermesatlas.com/projects/Shine8592/china-briefing GitHub: https://github.com/Shine8592/china-briefing Category: Skills & Skill Registries Stars: 0 多尺度中文资讯简报技能 - Multi-scale Chinese news briefing generator for Hermes Agent. From global to street level, with quality gates and AI analysis. China Briefing is a multi-scale Chinese news briefing generator designed for Hermes Agent. It generates structured reports ranging from global to street-level geographic scales using Tavily API for web searches. Highlights: - Supports multiple geographic scales from global to street level - Generates structured reports with core conclusions and action suggestions - Integrates user interests via semantic memory for search expansion --- ## pomponchik/incontext URL: https://hermesatlas.com/projects/pomponchik/incontext GitHub: https://github.com/pomponchik/incontext Category: Plugins & Extensions Stars: 0 Exact dynamic output budgeting for Hermes Agent incontext is a Hermes Agent plugin that dynamically budgets output space against the active context boundary. It inserts an output cap when remaining space meets a configured reserve or caller-supplied limit, otherwise leaving the request unchanged to avoid truncated responses. Highlights: - Budgets output space against Hermes' active context boundary. - Uses a two-stage preflight and middleware policy for token management. - Supports automatic context compression and provider-aware token counting. --- ## 181079342/hermes-memoss URL: https://hermesatlas.com/projects/181079342/hermes-memoss GitHub: https://github.com/181079342/hermes-memoss Category: Developer Tools Stars: 0 hemes 的memos记忆插件 MemOS Memory Plugin for Hermes Agent connects to a self-hosted MemOS instance to provide persistent memory storage. It enables semantic search, fact extraction, and automatic synchronization of conversation turns. Highlights: - Supports semantic search and multi-dimensional memory storage. - Includes a circuit breaker for MemOS API outages. - Provides tools for searching, adding, and deleting memories. --- ## aidatatools-dev/astro-agents-mcp URL: https://hermesatlas.com/projects/aidatatools-dev/astro-agents-mcp GitHub: https://github.com/aidatatools-dev/astro-agents-mcp Category: Skills & Skill Registries Stars: 0 Deterministic Western + Vedic astrology MCP server for AI agents. JPL DE440, no LLM, SHA-256 verifiable results. x402 + MPP. Astro Agents provides a hosted MCP server and REST API for Western and Vedic astrology calculations. It returns structured results with stated calculation conventions and SHA-256 input and result hashes; the repository documents the service and includes its MCP registry manifest. Highlights: - Resolves time zones and historical offsets from coordinates. - Offers tools for charts, transits, aspects, and Vedic calculations. - Supports MCP and REST; REST payments use x402 or MPP.