mem0ai / mem0
A universal memory layer providing multi-level retention for users, sessions, and autonomous agents. It utilizes hybrid retrieval and temporal reasoning to rank memories by relevant dates and states.
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.
A universal memory layer providing multi-level retention for users, sessions, and autonomous agents. It utilizes hybrid retrieval and temporal reasoning to rank memories by relevant dates and states.
An open-source context database that uses a filesystem-based directory paradigm and tiered L0/L1/L2 loading. This approach significantly reduces token usage while improving task-completion rates via recursive directory retrieval.
A high-performance memory engine featuring sub-300ms recall and byte-level deduplication for prompt-cache discounts. It automates user profile maintenance and includes native connectors for Notion, GitHub, and Google Drive.
An opinionated brain for Hermes Agent that synthesizes cited answers with explicit gap analysis of missing information. It features a self-wiring knowledge graph for complex entity traversal and MCP support for tools like Cursor and Claude Code.
A learning-focused memory system implementing retain, recall, and reflect workflows for long-term knowledge. It offers a simple LLM wrapper for automatic storage and supports enterprise backends like PostgreSQL and Oracle AI Database.
A memory provider that treats context as a git repository, allowing for branching, merging, and versioning of markdown context trees. It delivers sub-100ms retrieval across a 5-tier system and includes built-in tools for code execution.
A stateful agent library that extracts reasoning-based conclusions rather than relying on simple vector matching. It maintains evolving representations of users and projects in prompt-ready formats compatible with OpenAI and Anthropic.
A recursive self-improving context harness that uses five specialized agent roles to generate structured playbooks. It enables persistent knowledge transfer through CLI-first skill exports for Hermes Agent.
A zero-dependency, SQLite-backed memory system delivering sub-millisecond performance. It combines vector similarity, FTS5, and importance scoring in an MCP-ready integration.
A lossless context management plugin utilizing a hierarchical summary DAG for depth-aware compaction. It preserves raw messages in SQLite and provides dedicated tools like lcm_grep for precise retrieval.
A self-hosted backend for Honcho that enables private, cross-session persistence for Hermes Agent. It supports local inference servers and any OpenAI-compatible LLM via a Docker-based setup.
A local-first context engine that operates without API keys or cloud dependencies. It employs a hybrid retrieval system combining BM25, vector search, and knowledge graphs.
A portable identity and memory layer that ensures state continuity across Hermes Agent, Claude Code, and OpenClaw. It uses SQLite and markdown for local data ownership and hybrid graph-vector retrieval.
A shared memory layer for multi-agent systems using an open YAML engram format. It implements ACT-R activation to strengthen relevant facts and decay stale information without API costs.
A context optimization tool that increases cache hits and reduces prefill latency through prefix reordering and deduplication. It is designed to accelerate inference across SGLang, vLLM, and the Hermes ecosystem.
A memory kernel stack that consolidates temporal continuity, graph truth, and corpus retrieval. It leverages SQLite, Kuzu, and Chroma to provide bounded evidence packing that reduces prompt noise.
A reflective memory system featuring semantic search and ranked graph traversal. It automatically indexes local directories and URLs, using edge tags to create navigable relationships with inverse links.
An embedded, self-maintaining plugin that provides explainable recall via why_retrieved tags. It tracks contradictions and handles canonicalization without requiring a separate server or GPU.
An anticipatory memory system that prefetches context by monitoring agent session logs. It uses a local-first SQLite-vec storage and an MCP-native server for seamless integration with coding agents.
A utility that reduces prompt overhead by using BM25-based ranking to select only the most relevant tool schemas. It includes a dashboard to monitor token savings across hybrid and Anthropic Tool Search modes.
A local-only plugin using a columnar .lbdb embedded graph database. It employs importance-weighted recall to surface high-priority memories and supports GLiNER2 for entity extraction.
A pull-model episodic memory plugin that ensures complete deletion of memories without leaving persistent summaries. It provides a trace.jsonl audit log to track every memory operation for transparency.