adoresever/graph-memory
Deepseek Harness、Openclaw知识图谱记忆插件。2026年4月受邀发布在清华大学讨论会。Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, ena
- Stars
- 662
- Forks
- 99
- Open issues
- 18
- Last push
- 22d ago
About graph-memory
graph-memory is a free, open-source AI coding tool by adoresever, written mainly in TypeScript. Deepseek Harness、Openclaw知识图谱记忆插件。2026年4月受邀发布在清华大学讨论会。Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, ena. It has 662 GitHub stars and 99 forks, and was last updated 22d ago. It's released under the MIT license, a standard open-source license.
- License
- MIT
- Language
- TypeScript
- Stars
- 662
- Last update
- 22d ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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graph-memory FAQ
Is graph-memory free?
Yes. graph-memory is open source and free to use. It's released under the MIT license, a standard open-source license.
Does graph-memory run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does graph-memory need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is graph-memory still maintained?
Yes. It was last updated 22d ago and has 18 open issues on GitHub.
What are alternatives to graph-memory?
Similar free, open-source tools include Understand-Anything, claude-mem, graphify, archify.