Self-hosted memory service for AI agents that work in teams, written in Rust: layered L0→L3 memory, async LLM distillation, hybrid BM25 + vector recall, and department/team/member isolation. SQLite or
Self-hosted, team-aware long-term memory for AI agents. AgentMemory gives Claude Code, Codex, Antigravity, Hermes and any MCP client a memory that persists across sessions. It captures each conversation, distils it into facts, scenes and a persona in the background, and recalls what is relevant before every prompt. It all runs on your own servers.
- Your data stays with you. Memory, database and even the distillation model can all run inside your network. There is no dependency on any vendor's cloud service: any OpenAI-compatible endpoint works, including self-hosted models, as does a local CLI such as claude, codex or agy. - Built for teams, not just one user. A server holds departments, a department holds teams, and a team holds members and their agents. - Each member's conversations and facts stay private. - The scenes and persona of an agent are shared by the people who use it. - Team leaders see how distillation is doing without reading anyone's memory. - See COLLABORATION.md. - Memory that compounds. Raw turns (L0) are distilled into facts (L1), consolidated into scenes (L2) and summarised into a persona (L3). Recall combines BM25 and vector search with rank fusion. See How memory works. - Built to be operated. - A Monitor Panel with distillation health, generation logs and dead letters that expire and retry on their own. - SQLite to start, PostgreSQL with pgvector and Redis to scale. - Versioned storage migrations, and an upgrade.sh that backs up first. - One client for every agent. The amem CLI plugs into Claude Code, Codex, Antigravity and Hermes hooks, and serves
From the project README.
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