gitgoblin MCP server

gitgoblin

Find open-source projects worth your time, work out what they really need, and turn that into a pull request a maintainer would be glad to merge.

Website · Getting started · Use it from your agent · Contributing

gitgoblin is a free, open-source companion for contributing to other people's software. It is for anyone who wants their open-source time to count: a first contribution, a project to learn from or depend on, or a quiet project worth reviving. It digs through public repositories for work that matters, shows the evidence, and helps you do that work to the project's own standards.

Status: preview. Discovery and analysis work today; preparing a contribution with an AI agent is experimental. Nothing is on npm yet, so the command runs from a clone, and the MCP server installs from a GitHub release. See what works today.

Why

Finding somewhere to contribute usually means sorting by stars and searching for "good first issue". That surfaces the same crowded projects everyone else found, and misses the quiet library your own app depends on, the tool whose CI broke last month, and the docs that stopped matching the code two releases ago.

gitgoblin looks for those instead. It ranks projects against what you want, reads a repository the way a careful new maintainer would, and only proposes work it can back with evidence. When it writes code, the project's own tests have to pass, an independent reviewer checks the change, and nothing is published until you say so.

How it works

1. Discover. Rank public repositories for a goal (contribute, learn, adopt, revive, explore), with filters for language, topic and stars, or "more like this one". Every result says why it ranked where it did.
2. Understand. Profile a repository: what it is, how it is built and tested, how it treats outside contributors, and which conventions it follows.
3. Find the work. List concrete opportunities, each with evidence you can check: issues nobody is working on, CI about to break, docs that contradict the code, tests missing where the code changes most.
4. Contribute. For one opportunity, an AI agent investigates, plans, implements, runs the project's checks against a baseline, and gets an independent review. You read the result and decide whether to open the pull request.

Try it

You need Node.js 24 or newer and git. Run it from a clone:

git clone https://github.com/anandkaranubc/gitgoblin.git
cd gitgoblin
npm install
npx gitgoblin discover contribute --language typescript

That prints ten ranked repositories with the reasons behind each ranking. To see every signal for one repository:

$ npx gitgoblin explain BurntSushi/ripgrep --goal adopt
BurntSushi/ripgrep  ★ 69k · Rust · Unlicense  score 0.73
goal: adopt

activity              █████████░ 0.92 +0.05  last change today, 178 pull requests in the past year
responsiveness        ██░░░░░░░░ 0.16 −0.04  issues close in ~25 days, pull requests in ~45 days
busFactor             ██████░░░░ 0.58 +0.01  406 contributors, top committer wrote 70%

No configuration is needed; a GitHub token, or a gh login, raises the rate limit and adds data. docs/getting-started.md goes from here to analyzing a repository and preparing a contribution.

Use it from your AI agent

gitgoblin also runs as an MCP server, so the agent you already use can discover repositories, analyze them and brief you on one piece of work. For Claude Code:

claude mcp add gitgoblin -- npx -y https://github.com/anandkaranubc/gitgoblin/releases/download/mcp-v0.1.6/gitgoblin-mcp-0.1.6.tgz

Shortened. The full README is on GitHub.