[GitHub Trending] rohitg00/agentmemory
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Persistent memory for AI coding agents, directly addresses agent orchestration needs.
agentmemory is an open-source persistent memory engine for coding agents (Claude Code, Cursor, Gemini CLI, etc.) that eliminates re-explaining context across sessions via MCP, hooks, or REST API. It automatically captures agent actions, compresses them into searchable memory using BM25 + vector + graph search (RRF fusion), achieving 95.2% R@5 on LongMemEval-S—outperforming mem0 (68.5%) and Letta (83.2%)—while consuming only ~1,900 tokens/session ($10/yr with local all-MiniLM-L6-v2 embeddings). Built on iii engine with SQLite, no external dependencies, and v0.9.0 adds a filesystem connector and audit policy.
Integrate agentmemory as a shared memory server for all your MCP-compatible coding agents to eliminate session context loss and reduce token costs by 10x.
For a senior engineer building agent orchestration, this solves the critical problem of context loss across sessions, enabling agents to retain project-specific knowledge without manual re-teaching or expensive LLM summarization.