#668 · Primary category： AI Agents & Automation
MindMemOS
An AI agent memory system that accurately remembers context, evolves via interactions, and distills reusable skills for continuous capability growth.
Project last updated：08/29/26
GitHub Stars
965
Forks
95
Contributors
11
License
MIT
Why we included this project
Agents that lose their context between sessions are the frustration MindMemOS takes on. It runs as a self-hosted FastAPI service that gives agents a long-term memory layer, storing conversations, files, tool traces, and feedback so a session can resume where it left off instead of starting from a blank slate every time. It also watches for recurring patterns and promotes them into skill candidates, then pushes execution results and failures back into memory, which is how the system learns from experience. A Python SDK and plugins for harnesses like OpenClaw and DeepSeek Harness mean it slots into an existing stack without much rewiring. The paper and API docs make it approachable for teams who want to run and extend their own memory backend.
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