memU Personal Memory
A shared, searchable memory layer that turns coding-agent session history into reusable Markdown skills.
What does this agent do, and when should you use it?
memU is a personal memory system that stores knowledge as a shared LLM wiki across sessions, agents, and devices. It runs as host-specific sidecars such as memu-codex, memu-claude-code, and memu-agent, mining local session histories. A scheduled bridge creates jobs from new sessions, while the host agent decides whether to create, update, or leave Markdown skills unchanged; MemoryService itself makes no LLM or chat calls. Submitted skills are embedded and stored on the skill track, then surfaced through progressive_retrieve for related future work. The shared backend can be local SQLite, Postgres, or memU Cloud.
Host adapters read known transcript sources, including ~/.codex/sessions/**/*.jsonl for Codex, project JSONL files for Claude Code, and read-only SQLite data for OpenClaw and Hermes. In the record path, prepare slices a session into self-contained self-evolve jobs containing context and file paths; the agent reviews related skills and either does nothing, patches an existing skill, or writes a new Markdown skill. commit sends disk changes through commit_results, after which MemoryService embeds the skill name and description and stores it on the skill track. The inject path patches a host instruction file so the agent runs <binary> retrieve before answering, returning relevant memory through progressive_retrieve. For unlisted hosts, memu-agent detect probes for recognizable JSONL logs and instruction files, while <binary> doctor checks configuration, selected mode, and a live retrieval.
- A Codex user who wants recurring project decisions and workflows from ~/.codex/sessions to inform later coding tasks.
- A developer alternating between Claude Code and Cursor who wants skills learned in one configured host to be retrieved by another.
- A privacy-conscious individual working on one machine who prefers a user-controlled SQLite or Postgres store over a cloud memory backend.
- An operator of OpenClaw, Hermes Agent, or WorkBuddy who wants to derive reusable skills from existing SQLite or JSONL session history.
- A user of an unsupported command-line agent who wants memu-agent detect to establish whether transcript capture and retrieval injection are possible.
What are this agent's strengths and limitations?
- It connects transcript capture, skill distillation, and future retrieval, with readable and editable Markdown skills as the durable output.
- Dedicated adapters cover Codex, Claude Code, Cursor, OpenClaw, Hermes Agent, WorkBuddy, and Cola, while memu-agent detect provides a documented path for other recognizable JSONL hosts.
- A single ~/.memu/config.env lets configured hosts share memory across tools, with SQLite, Postgres, and memU Cloud storage options.
- The memory service is limited to storing, embedding, and retrieving agent-prepared skills rather than independently making chat or LLM calls.
- Host integration requires access to local session logs and changes to host instruction files, which should be reviewed before adoption.
- Self-hosting still requires an embedding provider and API key; documented providers include OpenAI, Jina, Voyage, Doubao, and OpenRouter.
- Support varies by host and operating system: ChatGPT Chat and Claude Chat/Cowork are unsupported, and Linux Codex is listed as retrieval-only.
- SQLite uses brute-force cosine search and is intended for a single writer; concurrent or larger stores require Postgres, pgvector, and the optional postgres package.
How do you install or deploy this agent?
Python 3.11+ is documented. Install the CLI with pip install memu-cli; alternatives are npx memu-cli --help and uvx --from memu-cli memu. For Cloud mode, obtain an API key from memu.so and use the binary for the relevant host. For self-hosting, configure ~/.memu/config.env: host adapters require MEMU_DB, and the documented embedding settings are MEMU_EMBED_PROVIDER, MEMU_API_KEY, MEMU_EMBED_MODEL, plus optional MEMU_BASE_URL. Use MEMU_MEMORY_MODE to select Local or Cloud; an unset value remains Local for backward compatibility. After host setup, run <binary> doctor to verify the resolved configuration and retrieval path.
How do you use this agent?
After setup, the registered bridge captures new sessions and the patched host instruction file directs the agent to retrieve memory before it answers. A manual lookup is memu-codex retrieve "What should I remember about this project?"; use memu-claude-code, memu-cursor, memu-openclaw, memu-hermes, memu-workbuddy, or memu-agent for the corresponding host. For a host without a dedicated binary, run memu-agent detect first to see what transcript and instruction-file seams were found. Set MEMU_DB to a SQLite or Postgres DSN for local storage; Postgres requires pip install "memu-cli[postgres]".
How does this agent compare with similar options?
Unlike keeping context inside one assistant, memU shares learned session knowledge among configured hosts through one backend. Compared with memU Cloud, self-hosting stores memory in user-configured SQLite or Postgres, though it still requires an embedding provider.