I built metaBrain, an open-source local memory store for AI agents
Hi r/OpenSourceAI,
I built metaBrain, an open-source local document memory for AI agents and developer workflows.
The project came from a problem I kept having while using agents for coding: useful context ends up scattered everywhere. Some of it is in markdown planning files, some in JSON state, some in scratch notes, some in task logs, and some in project-specific docs. Moving from one project to another gets tedious, and bootstrapping a new idea often means rebuilding the same context again.
metaBrain is my attempt to give that context one local, searchable place to live.
Documents are addressed with filesystem-like paths, for example:
/notes/today
/projects/foo/release-plan
/agents/openclaw/task-state
Under the hood they are stored in a local LevelDB-backed database with tags, metadata, lexical search, version history, zstd compression, JSONL export, and patch-based updates.
The CLI currently supports:
- put/get/list documents
- search by text, tags, and metadata
- patch documents with unified diffs
- inspect version history
- export the store as JSONL
- prune old versions
One goal was to make the tool discoverable by agents themselves. In my own workflow, I can point OpenClaw at the repo, ask it to discover the available commands, and then have it use `mb` directly as part of its task. That gives both me and the agent a shared local memory store instead of a pile of files spread across the workspace.
The repo is here:
https://github.com/OpenCow42/metaBrain
It is released under the permissive BSD 3-Clause license.
Install on macOS:
brew tap OpenCow42/tap && brew install mb
Example:
mb init
mb put /notes/today "Remember this project context." --tag planning --meta source=agent
mb search "project context"
mb get /notes/today
It is early. Right now it is a Swift package with a CLI and embeddable core library. I’m also planning a native Mac app to browse and inspect the database visually.
I’d be especially interested in feedback from open-source AI/tooling people:
- Is this useful as a local-first alternative to scattered agent memory files?
- Would an MCP server be the most useful next integration?
- What would make this easier or safer for agents to use autonomously?