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memU

NevaMind-AI · NevaMind-AI/memU

Provides a lightweight, agent-driven personal memory system that acts as a shared LLM wiki across different agents and devices.

Personal memory across agents

15k stars1.1kLicense: No licenseUpdated 5 days ago0 opens

Preview

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What you can do with it

  • Enable an AI agent to recall previous conversations or decisions across new sessions.
  • Share learned skills and knowledge base seamlessly between multiple AI agents.
  • Build a persistent, searchable knowledge base from agent interactions and tasks.

Safety check

Caution

Usable, but read the notes first.

  • ●No clear license: check with the author before using it in a commercial product.

Automated scan of the repo files. Always review code you run.

From the README

memU

Personal memory, stored as Wiki

Across Sessions. Across Agents. Across Devices.


memU is a lightweight, agent-driven memory system that gives users a shared LLM wiki across sessions, agents, and devices. It automatically distills your own reusable skills from your agent history. Its core memory logic is only 500 lines — compact enough to inspect, understand, and adapt.

Quick start

memU works with Codex, Claude Code, Cursor, OpenClaw, Hermes, WorkBuddy, Cola, pi, and more. See Host adapters.

Cross-device · Free · Unlimited · View online

Get your API key from memu.so, then send this message to your agent:

Read https://memu.pro/SKILL.md, follow its instructions to install and configure memU, API Key is memu_•••••••••(get Api Key from memu.so).

Agent support

This matrix lists the currently tested memU integrations by operating system.

  • Memorize — capture useful session knowledge through a scheduled background task and turn it into reusable memory.
  • Retrieve — bring relevant memory into a future task.
  • ⚠️ — supported with an important limitation; see the user note.

macOS

AgentModeMemorizeRetrieveUser note
ChatGPTChatGPT(Work mode), codex and VS Code extension✅✅
ChatGPTChat❌❌Chat mode is not currently supported. Please use Work mode.
Claude CodeDesktop and CLI✅✅If the selected model declines the setup steps, retry with Opus or another model. Sonnet 5 can occasionally do this.
ClaudeChat and Cowork❌❌
Cursor—✅✅
OpenClaw—✅✅Retrieve support has not yet been verified.
Hermes Agent—✅✅
WorkBuddy—✅✅

Windows

AgentModeMemorizeRetrieveUser note
ChatGPTChatGPT(Work mode), codex and VS Code extension✅✅
ChatGPTChat❌❌Chat mode is not currently supported. Please use Work mode.
Claude CodeDesktop and CLI✅✅If the selected model declines the setup steps, retry with Opus or another model. Sonnet 5 can occasionally do this.
ClaudeChat and Cowork❌❌
Cursor—✅✅
OpenClaw—✅✅
Hermes Agent—✅⚠️Use a memU version with Windows HERMES_HOME support; older versions may retrieve from the wrong files.
WorkBuddy—✅✅With Hy3, retrieval may fail. Retry with another model if this happens.

Linux

AgentModeMemorizeRetrieveUser note
CodexVS Code extension❌✅
Claude CodeCLI✅✅
OpenClaw4.23 / 7.1✅✅

Support status reflects the current release and may change as host integrations evolve.

How it works

Automatic skill extraction

Once the scheduled bridging task is installed, memU can turn useful agent history into reusable Markdown skills automatically.

  1. Capture new sessions. The host adapter reads new session history, including messages and tool calls.
  2. Prepare self-evolve jobs. prepare slices each session into a self-contained job with the paths and context the agent needs.
  3. Let the agent decide. The agent reads related existing skills, then chooses to do nothing, patch an existing skill, or create a new one.
  4. Write readable skill Markdown. Each skill has a name, description, and reusable workflow, including useful branches, edge cases, and pitfalls.
  5. Commit and index. commit submits changed skill files through commit_results; memU embeds the skill name and description and stores it under the skill track.
  6. Retrieve it later. On a similar future task, memU returns the relevant skill so any connected agent can use the learned workflow.

The judgment and synthesis stay inside the agent. MemoryService makes no LLM or chat calls; it stores, embeds, and retrieves the skill Markdown the agent prepared.

Self-hosted

Private · Single-device · Embedding key required

To run memU locally with your own storage and embedding provider, send this message to your agent:

Read https://raw.githubusercontent.com/NevaMind-AI/MemU/main/SKILL.md and follow it to install memU.

Uninstall

To uninstall memU, send this message to your agent:

Read https://memu.pro/SKILL.md and follow its instructions to uninstall memU.

By default, uninstalling removes the host integration and tooling while keeping your memory store and ~/.memu/config.env, so a later reinstall can resume where you left off. Memory is erased only when you explicitly ask for it.

Host adapters: memory for desktop coding agents

memU runs as a sidecar to a desktop agent, one binary per host. Each binds two seams:

  • record — a scheduled bridging task slices new session logs into self-contained job files; the agent itself distills them into memory/skill Markdown; commit submits whatever the agent left on disk back through commit_results.
  • inject — a standing instruction in the host's instruction file tells the agent to run <binary> retrieve (→ progressive_retrieve) before answering.
HostBinarySession log it minesInstruction file it patches
Codexmemu-codex~/.codex/sessions/**/*.jsonl~/.codex/AGENTS.md
Claude Codememu-claude-code~/.claude/projects//<session>.jsonl~/.claude/CLAUDE.md
Cursor (Agent/CLI)memu-cursor~/.cursor/projects//agent-transcripts/**.jsonl./AGENTS.md (per project)
OpenClawmemu-openclaw~/.openclaw/agents//agent/openclaw-agent.sqlite (SQLite, read-only) + legacy /sessions/*.jsonl~/.openclaw/workspace/AGENTS.md
Hermes Agentmemu-hermes`~/.herme
View source on GitHub