mem0ai / mem0
The official Hermes Agent memory provider offering a universal memory layer for user, session, and agent state. It supports hybrid retrieval via semantic, keyword, and entity matching across managed cloud or self-hosted deployments.
The top community-built memory and context management tools for Hermes Agent, ranked by GitHub stars. Memory is what makes Hermes self-improving — these tools extend its built-in recall with long-term semantic memory, graph-based retrieval, and cross-session persistence.
For the architecture behind these tools, read The Hermes Agent Memory Guidebook.
The official Hermes Agent memory provider offering a universal memory layer for user, session, and agent state. It supports hybrid retrieval via semantic, keyword, and entity matching across managed cloud or self-hosted deployments.
An official Hermes Agent memory provider featuring a custom vector graph engine and byte-level deduplication for high-efficiency recall. It automates fact extraction and integrates with external connectors like Google Drive, Notion, and GitHub.
An official Hermes Agent memory provider that uses a tiered L0/L1/L2 loading system to significantly reduce token consumption. It organizes memories via a filesystem-based structure and provides visualized retrieval trajectories for debugging.
An opinionated brain for Hermes Agent that synthesizes cited answers and performs explicit gap analysis on missing information. It utilizes a self-wiring knowledge graph to handle complex entity relationship queries and scoped multi-user access.
A learning-focused memory system that implements retain, recall, and reflect workflows for long-term agent growth. It acts as an LLM wrapper that automates storage and retrieval across providers like OpenAI, Anthropic, and Ollama.
A reasoning-first memory library that extracts conclusions from conversations to build stateful agents. It employs peer-centric modeling and a hybrid search combining BM25 and vector retrieval.
An official Hermes Agent memory provider that treats context as a git repository, enabling versioning via commits, branches, and merges. It features a 5-tier retrieval system for sub-100ms latency and supports cloud sync for team knowledge sharing.
A recursive self-improving context harness that uses real-world evaluation and feedback loops to optimize agent performance. It generates persistent playbooks and structured execution traces across various providers including Claude Code and MCP.
A zero-dependency memory system providing sub-millisecond retrieval latency using SQLite storage. It features a temporal knowledge graph and episodic memory compression with native MCP support for AI clients.
A lossless context management plugin that uses a hierarchical DAG to compact conversation history without losing detail. It provides specialized tools for grepping and expanding summaries stored in a local SQLite database.
A self-hosted backend for the Honcho library that enables private cross-session persistence for Hermes Agent. It supports any OpenAI-compatible LLM and includes automated Docker, PostgreSQL, and Redis setup scripts.
A local-first identity and secrets layer that provides portable state across Hermes Agent and other MCP clients. It features a repairable memory system allowing users to edit, delete, or reclassify agent context via SQLite.
A shared memory layer for multi-agent systems using an open YAML engram format to eliminate API costs. It utilizes ACT-R activation to strengthen relevant facts while decaying stale information over time.
An on-device context engine that operates entirely locally without cloud dependencies or API keys. It combines BM25, vector search, and knowledge graphs via MCP server and Claude Code hooks.
A context optimization tool that increases prefill speed by 1.5–3× through prefix cache reuse. It reduces prompt token usage by approximately 36% and provides native plugin support for Hermes Agent.
An embedded, self-maintaining memory plugin that provides explainable recall via 'why_retrieved' tags. It includes first-class contradiction tracking and canonicalization without requiring a separate server or GPU.
A memory kernel stack that consolidates temporal continuity, graph truth, and corpus retrieval. It leverages a multi-layered storage approach using SQLite, Kuzu, and Chroma to provide bounded evidence packing.
A reflective memory system combining semantic search with ranked graph traversal. It automatically indexes local directories, URLs, and multimedia files using edge tags to create navigable relationships.
An anticipatory memory system that prefetches context by monitoring agent session logs. It uses local-first storage with SQLite-vec and GGUF models via an MCP-native server.
A utility that reduces prompt token overhead by using local BM25 ranking to select only relevant tool schemas. It includes a dashboard to track token savings and is compatible with Hermes Agent v0.14.0.
A local-only plugin using an embedded .lbdb graph database with importance-weighted recall to surface high-priority memories. It supports BM25 keyword search and optional GLiNER2 entity extraction.
A pull-model episodic memory plugin that ensures complete deletion of events to prevent persistent summaries from haunting future recall. It provides a trace.jsonl audit log for every memory operation.
A plugin that integrates Exabase M-1 for self-organizing long-term agent memory. It provides tools for manual storage and searching, featuring configurable query expansion and result reranking.