loading…
Search for a command to run...
loading…
A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directo
A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep
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.
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.
your-repo/
├── .ai-memory/
│ ├── README.md # explains the convention
│ ├── facts.jsonl # append-only structured facts with evidence
│ ├── decisions/ # one markdown per non-trivial decision
│ │ └── 2026-05-19-pick-httpx.md
│ └── gotchas.md # one-line "watch out for X" notes
├── src/
└── README.md
Pure files. Sync over git. No daemon, no DB, no auth. Works offline.
pip install repo-memory-mcp
# or
uvx repo-memory-mcp --help
Python ≥3.10. Depends only on the official mcp SDK (for the MCP server).
cd your-repo
repo-memory init # creates .ai-memory/ + adds CLAUDE.md hint
repo-memory add-fact "Auth middleware lives in src/auth/middleware.py" \
--file src/auth/middleware.py --lines 42-180 --tool grep
repo-memory add-decision "Use httpx not requests" \
--body "HTTP/2 + async support; we already use anyio."
repo-memory add-gotcha "Don't run migrations during 9-11am UTC peak"
repo-memory show # render everything as Markdown
repo-memory list-facts --tag auth
Then commit .ai-memory/ like any other file:
git add .ai-memory/
git commit -m "memory: record auth middleware location + httpx decision"
git push
Anyone else (human or AI) who pulls the repo now sees those facts/decisions immediately.
For agents discovering this repo through search or MCP indexing.
repo-memoryrepo-memory) and MCP stdio (repo-memory-mcp)..ai-memory/ in the repo. Sync = git.| Tool | When |
|---|---|
get_repo_memory |
At the start of any task on this repo. |
add_fact |
After you verify a non-obvious fact (location, behavior, convention). Include evidence so the next agent can re-verify cheaply. |
add_decision |
After a non-trivial choice (architecture, library, trade-off). Body should explain why, not just what. |
add_gotcha |
After a surprise that wasted your time. |
list_facts |
When you want only facts in a specific area (tag, source_file). |
1. agent.call("get_repo_memory") -> absorb prior context
2. ...do task, run tools, verify things...
3. agent.call("add_fact", claim, evidence) -> for each new fact
4. agent.call("add_decision", title, body) -> if a choice was made
5. session ends, human commits .ai-memory/ -> shared via git
Add to your client config (Claude Desktop / Cursor / Cline):
{
"mcpServers": {
"repo-memory": {
"command": "uvx",
"args": ["repo-memory-mcp", "--repo", "/abs/path/to/the/repo"]
}
}
}
Or set REPO_MEMORY_ROOT env var instead of --repo.
Exposes 5 tools: get_repo_memory, add_fact, list_facts,
add_decision, add_gotcha.
git blame tells you which agent added which fact and when.facts.jsonl — one JSON object per line:
{
"id": "abc123def456",
"ts": "2026-05-19T18:00:00Z",
"claim": "Auth middleware lives in src/auth/middleware.py",
"evidence": {
"file": "src/auth/middleware.py",
"lines": "42-180",
"tool": "grep",
"command": "rg 'def authenticate' src/",
"verified_at": "2026-05-19T18:00:00Z"
},
"tags": ["auth"],
"added_by": "claude-opus-4.7"
}
Append-only. Stale entries stay. Readers consult verified_at and
re-verify if they want.
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.
| Command | Effect |
|---|---|
repo-memory init [--no-claude-md] |
Create .ai-memory/ skeleton + (default) update CLAUDE.md/AGENTS.md. |
repo-memory show [--limit N] |
Print everything as one Markdown doc. |
repo-memory add-fact "<claim>" [--file F --lines L --tool T --command C --tag T --by AGENT] |
Append a fact. |
repo-memory list-facts [--tag T] [--source-file F] [--since ISO] [--limit N] [--json] |
List/filter facts. |
repo-memory add-decision "<title>" [--body MD] |
Write a decision file. |
repo-memory list-decisions |
List decision file paths. |
repo-memory add-gotcha "<note>" |
Append a one-line gotcha. |
All commands take --root PATH if your CWD isn't the repo root.
MIT © yubinkim444
Выполни в терминале:
claude mcp add repo-memory -- npx Query your database in natural language
автор: AnthropicRead-only database access with schema inspection.
автор: modelcontextprotocolInteract with Redis key-value stores.
автор: modelcontextprotocolDatabase interaction and business intelligence capabilities.
автор: modelcontextprotocolНе уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории data