clawdbrunner

clawdbrunner / openclaw-graphiti-memory

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Hybrid memory system for OpenClaw using Graphiti temporal knowledge graph

ai-agents clawdbot graphiti knowledge-graph memory
54
5
100% credibility
Found Feb 08, 2026 at 26 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

A hybrid memory system for OpenClaw AI agent teams that layers private notes, shared references, and a knowledge graph for improved recall and collaboration.

How It Works

1
🔍 Find smarter memory for AI helpers

You discover this add-on that lets your team of AI assistants remember personal notes, shared facts, and team knowledge all in one place.

2
📥 Run the easy setup

You grab the one-click installer which prepares folders and starts the shared thinking space in the background.

3
🚀 Memory layers come alive

Everything connects smoothly—private notes for each assistant, shared guides for the team, and a brain for key facts across everyone.

4
📝 Tell agents how to use it

You add simple notes to each assistant's guide so they know when to check memories or save new ones.

5
💾 Save your first facts

You jot down details like your preferences or team roles into the shared space to kick things off.

6
🧠 Assistants start sharing wisdom

Your AI team now pulls up past notes, team info, and facts during chats, making them feel connected and smart.

🎉 Team works like magic

Your assistants coordinate effortlessly, recalling details from anywhere to give better help every time.

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Star Growth

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AI-Generated Review

What is openclaw-graphiti-memory?

This Shell-driven project adds a hybrid memory layer to OpenClaw multi-agent AI setups, blending QMD vector search on private/shared files, symlinked reference docs, and Graphiti's temporal knowledge graph on Neo4j. Agents get per-user facts via CLI tools like graphiti-search.sh for cross-group queries or graphiti-log.sh for logging discoveries, all spun up via Docker Compose with OpenAI embeddings. It solves siloed agent memory in team workflows, delivering unified recall like "user email from shared files" or "Piper's invoice findings from the graph."

Why is it gaining traction?

Stands out with hybrid search akin to github hybrid cache or github hybrid search tools, but tuned for AI agents—mix QMD docs and Graphiti facts in one memory-hybrid-search.sh command, at under $1/month cost. Docker one-shot deploy and auto-sync scripts (file watches, session imports) cut setup from hours to minutes, unlike pure vector stores lacking temporal edges. Devs dig the graphiti edge for "when did config change?" queries over flat embeddings.

Who should use this?

OpenClaw orchestrators managing 5+ agents for tasks like finance (roster checks), security (cross-agent alerts), or projects (temporal logs). Ideal for indie AI builders needing shared context without custom RAG pipelines, or teams extending blazor hybrid github apps with persistent agent state.

Verdict

Solid for OpenClaw users—MIT licensed, thorough README/setup, but 30 stars and 1.0% credibility signal early maturity; test in staging first. Grab it if multi-agent memory pains you, skip for generic LLM apps.

(198 words)

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