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yamantaka520/Agent-Memory-OS

Name: yamantaka520/Agent-Memory-OS
Author: Various

by Various

Local-first memory engine for AI-agent teams — private/team/project ACL, associative recall, federated sync, and a built-in MCP server. One SQLite file, no LLM required. Apache-2.0

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yamantaka520/Agent-Memory-OS

Added 3 Sept 2026

#agent#agent-memory#agents#ai#ai-agents#claude#knowledge-graph#llm

Catalogue record, not a reviewed recommendation. This record can include automatically collected descriptions and setup details. Confirm important claims with the original source. Explore source-reviewed tools.

Overview

Local-first memory engine for AI-agent teams. Provides private, team, and project access control, associative recall, federated sync, and a built-in MCP server. Stores everything in one SQLite file and does not require an LLM. Apache-2.0 licensed.

Best for

Best for
Teams building local-first AI agents that need shared memory without cloud dependencies

Use cases

Share agent memory across a team with access control
Sync memory between local and remote agent environments
Expose memory to agents through the built-in MCP server

How to use

Install

pip install 'agent-memory-os[full]'    # recommended: everything (Web UI, MCP, turbovec)

Clients listed in this record (not verified here)

Claude Code, ChatGPT

Notes

5 stars on GitHub. Last updated 2026-09-02. Licensed Apache-2.0.

Pros

Single SQLite file simplifies deployment and portability
No LLM dependency reduces cost and latency
Apache-2.0 license permits flexible reuse

Cons

Federated sync adds setup overhead for multi-device use
Associative recall is not semantic search without an LLM
Single-file storage limits horizontal scaling

Open-source & AI alternatives

Swap-in tools that solve the same job. Weigh the trade-offs before you commit.

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