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  3. Repo Memory MCP
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Repo Memory MCP

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe havenโ€™t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time โ€” check back soon.
View RepositoryVisit Website

Persistent local memory for MCP-compatible AI coding agents, stored per repository in SQLite.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

One-click editor setup isnโ€™t available for this listing yet โ€” we donโ€™t have a confirmed install command, and weโ€™d rather show nothing than point your editor at the wrong package or host. Follow the projectโ€™s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON โ–พ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself โ€” its README, its docs, or a verified owner. We havenโ€™t found those for repo-memory-mcp, and weโ€™d rather show nothing than a guess youโ€™d paste into your client. Follow the projectโ€™s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives๐Ÿ—„๏ธ More in Databases

Documentation Overview

repo-memory-mcp

mcp-name: io.github.Umarjaum/repo-memory-mcp

Persistent memory for AI coding agents

AI coding agents are powerful, but they forget repository-specific corrections, conventions, constraints, and architectural decisions. repo-memory-mcp gives MCP-compatible coding agents a persistent, local, repository-aware memory layer.

Teach your coding agent once. Let your repository remember.

Tests PyPI License

What it does

MCP hosts decide when tools are called; MCP does not automatically intercept every conversation. This project exposes explicit tools that let an agent load important context at session startup, search relevant memories, store corrections and decisions, update stale guidance, and archive obsolete memories.

The memory database lives in .repo-memory/memory.db inside the detected repository. It uses SQLite, deterministic local ranking, and no cloud service.

Why developers use it

  • Persistent project memory: corrections, rules, conventions, constraints, decisions, and bug-fix lessons survive sessions.
  • Repository-aware isolation: unrelated repositories do not share memory.
  • Local-first privacy: no API keys, remote database, external embeddings, telemetry, or background upload.
  • Explicit MCP workflow: the agent chooses when to remember and recall; there is no claim of automatic conversation interception.
  • Fast and inspectable: SQLite storage, JSON export, CLI diagnostics, and human-readable records.
  • Security-minded: likely API keys, bearer tokens, passwords, cloud credentials, and private keys are rejected by default.

Install and use in two minutes

The public PyPI distribution is named repo-memory-mcp-ai because the shorter repo-memory-mcp name is already owned by another project. The MCP server and GitHub project identity remain repo-memory-mcp.

Terminal
pip install repo-memory-mcp-ai
repo-memory doctor

Start the MCP server directly:

bash
repo-memory-mcp

Or run it without a permanent installation:

bash
uvx --from repo-memory-mcp-ai repo-memory-mcp

The server is local and communicates over stdio. It does not need an API key.

Configure an MCP client

The common stdio configuration is:

config.json
{
  "mcpServers": {
    "repo-memory": {
      "command": "uvx",
      "args": ["--from", "repo-memory-mcp-ai", "repo-memory-mcp"]
    }
  }
}

Use the client-specific configuration location and format documented by your MCP host. Ready-to-copy examples are in examples/:

  • claude-desktop.json
  • cursor.json
  • workflow.md

The project is vendor-neutral and is intended for Claude Code, Cursor, Cline, Windsurf, and other MCP-compatible coding agents. Compatibility depends on the hostโ€™s MCP support and configuration format.

Recommended agent workflow

At the beginning of a coding session, call get_startup_context(). When the developer corrects a repeated mistake, call remember_correction(topic, lesson). When a relevant question arises, call recall_memory(query). When guidance becomes stale, call update_memory() or archive it with forget_memory().

Example instruction to an agent:

text
At the start of this session, call get_startup_context. If I correct a repeated mistake or establish a durable project rule, store it with the appropriate repo-memory tool. Do not store credentials or transient chat context.

Available MCP tools

ToolUse it for
get_startup_contextLoad concise, high-value repository guidance at session start
remember_correctionStore a lesson learned from a correction or bug fix
remember_ruleStore a durable project rule or convention
remember_decisionStore an architectural decision and rationale
recall_memorySearch active memory with deterministic local scoring
list_project_rulesList active project rules
list_memoriesFilter memories by type or status
update_memoryCorrect an existing memory without creating a replacement
forget_memoryArchive obsolete memory for audit-friendly retention
export_memory / import_memoryMove validated memory between safe copies of the same repository

CLI

server.ts
repo-memory init
repo-memory list
repo-memory rules
repo-memory search "database migrations"
repo-memory export ./memory-backup.json
repo-memory import ./memory-backup.json
repo-memory doctor

Privacy and security boundaries

Memories stay on the machine running the server. This implementation does not require API keys, cloud accounts, remote databases, external embeddings, or telemetry. It only inspects text explicitly submitted to memory tools. Your operating system, package manager, backups, and MCP host may have separate behavior.

Likely secrets are rejected by default. Do not submit passwords, tokens, private keys, or credentials to memory tools. The .repo-memory/ directory is ignored by Git so private memory is not accidentally committed.

Development

bash
git clone https://github.com/Umarjaum/repo-memory-mcp.git
cd repo-memory-mcp
python -m venv .venv
. .venv/bin/activate
pip install -e '.[dev]'
pytest

Discovery and publishing

  • Project site: repo-memory-mcp.negoshades.workers.dev
  • Documentation: quickstart and tools
  • Client guides: Claude, Cursor, VS Code, Cline, and Windsurf
  • Extensions: VS Code and Bing-compatible browser companion
  • Contributions: open-source contribution guide
  • Source: GitHub
  • Package: PyPI
  • Registry metadata: server.json
  • Publishing guide: PUBLISHING.md

Developer

Muhammad Umar Jabbar โ€” Khanewal, Punjab, Pakistan. Personal website: umarjaum.netlify.app.

Roadmap

Future work may improve ranking, add confidence feedback, provide optional local embeddings, generate project context, add a memory inspection UI, and publish the companion extensions to official marketplaces. Team/shared memory remains explicitly opt-in.

Companion extensions

  • extensions/vscode provides local setup commands for VS Code.
  • extensions/bing provides a privacy-safe Manifest V3 context-menu helper for turning selected Bing research into a repo-memory prompt.

The browser companion intentionally does not invoke the local stdio MCP process. Direct browser-to-MCP integration would require a separately reviewed native-messaging bridge.

License

MIT. See LICENSE.

Read the full README โ†’View source on GitHub โ†’

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Reviews

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Frequently Asked Questions about Repo Memory MCP

We don't have a confirmed install command for repo-memory-mcp yet, so we don't publish a generated one โ€” a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/Umarjaum/repo-memory-mcp) for the current steps.

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Technical Specs & Signals

Category๐Ÿ—„๏ธDatabases
More technical detailsExpand โ–พ
Last updatedSep 28, 2026
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27Quality signal: Emerging ยท 27/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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