
Repo Memory
io.github.yubinkim444Published by GitHub account yubinkim444v0.2.1Updated Oct 24, 2026
Shared, git-tracked working memory for AI agents on the same codebase.
The publisher's own server: Memory.fit
Overview
A local MCP server that gives an assistant a shared, git-tracked memory store in a repository's .ai-memory/ folder, so facts, decisions and gotchas persist for.
- What you can do
- Read the repository's stored memory at the start of a task to absorb prior context and conventions. Append verified facts with evidence such as file, line range and tool used. List and filter facts by tag or source file. Record non-trivial decisions as markdown files explaining the reasoning. Add short gotcha notes about surprises worth avoiding. Initialize the memory folder and optionally append a discovery hint to CLAUDE.md or AGENTS.md.
- When to use it
- Useful when several AI sessions or tools work on the same codebase and keep rediscovering the same conventions, file locations and past decisions. It suits teams that want that knowledge reviewed and shared through normal git commits rather than a hosted service.
- Requirements
- Runs locally as a Python package (Python 3.10 or newer) via uvx or pip, with the official mcp SDK as its only dependency. Needs the path to the target repository, given with the --repo argument or the REPO_MEMORY_ROOT environment variable, which defaults to the current working directory. No account, API key or network access is required.
Installation
In SourceWeft
- Open Repo Memory in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
repo-memory
Shared, git-tracked working memory for AI agents that share a codebase. What one Claude / Cursor / Cline learns about your repo, the next one picks up automatically. No database. No SaaS. Just files in your repo.
[PyPI] [Python] [MCP] [License: MIT]
The problem
Every AI session that touches your repo starts from zero. It re-greps the same files. It re-discovers the same conventions. It re-asks the same questions you already answered three sessions ago. Multi-user / multi-tool makes it worse: your teammate's Cursor and your Claude Code learn the same codebase independently.
There is CLAUDE.md / .cursorrules for rules the human writes. But
there is nothing for facts an agent verified — "the auth middleware
lives at src/auth/middleware.py:42", "PR #387 chose httpx over requests
because of HTTP/2", "don't run migrations during peak hours".
repo-memory is that nothing. A .ai-memory/ directory you commit to
your repo. Every AI tool reads from it, writes to it. Git is the database.
Layout
Pure files. Sync over git. No daemon, no DB, no auth. Works offline.
Install
Python ≥3.10. Depends only on the official mcp SDK (for the MCP server).
Quick start
Then commit .ai-memory/ like any other file:
Anyone else (human or AI) who pulls the repo now sees those facts/decisions immediately.
LLM & AI Agent Readable Specification
For agents discovering this repo through search or MCP indexing.
Identity
- name:
repo-memory - purpose: read/write a structured, git-tracked memory store about the current codebase so multiple AI agents (and humans) don't re-learn it.
- transport: CLI (
repo-memory) and MCP stdio (repo-memory-mcp). - storage: plain files under
.ai-memory/in the repo. Sync = git.
When to call which tool
Recommended agent workflow
MCP server install
Add to your client config (Claude Desktop / Cursor / Cline):
Or set REPO_MEMORY_ROOT env var instead of --repo.
Exposes 5 tools: get_repo_memory, add_fact, list_facts,
add_decision, add_gotcha.
Why git, not a database
- Zero infra. No service to host, no account to create, no API key to rotate.
- Already authoritative. Git history is the single source of truth.
git blametells you which agent added which fact and when. - Works offline. Plane, train, conference WiFi — all fine.
- PR review. Suspicious or wrong facts get filtered through normal code review.
- Per-repo scope. A fact about repo A doesn't leak into repo B; the store is local to the repo.
Schema (for tooling authors)
facts.jsonl — one JSON object per line:
Append-only. Stale entries stay. Readers consult verified_at and
re-verify if they want.
Automatic discovery hint
repo-memory init also appends a short discoverability section to your
repo's CLAUDE.md (or AGENTS.md if you already have one) telling any
AI agent that enters the repo to check .ai-memory/ first and to record
new findings back into it. Idempotent — re-running won't duplicate.
Opt out with --no-claude-md.
The appended block is delimited by <!-- BEGIN: repo-memory --> and
<!-- END: repo-memory -->, so you can hand-edit other parts of your
CLAUDE.md freely.
CLI reference
All commands take --root PATH if your CWD isn't the repo root.
About the author
Built by yubinkim444, who also makes Kay's Records — an app for iOS and Android.
If this project saved you time, giving the app a try is the nicest way to say thanks.
License
MIT © yubinkim444
Source: README.md at commit 167f6bd
Tools
0Version history
1- v0.2.1LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
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