GitHub MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GitHub MCP ServerGet the stats for facebook/react"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
🤖 GitHub MCP Server — Your AI-Powered GitHub Assistant
Ask Claude anything about a GitHub repo — and it actually does it.

What is this?
This is a Model Context Protocol (MCP) server that connects Claude AI directly to the GitHub API.
Instead of copy-pasting repo links and asking Claude to "analyze this", you just talk to Claude naturally:
"Get the stats for facebook/react" "Find good first issues in microsoft/vscode" "Summarize PR #42 for vercel/next.js"
And Claude calls the right tool, fetches live data from GitHub, and gives you a clean, formatted answer — all inside Claude Desktop.
No browser switching. No manual copy-paste. Just ask.
Related MCP server: GitHub MCP Server
Tools Available
Tool | What it does |
| Stars, forks, language, license, last push — everything at a glance |
| Lists open issues with labels, age, and comment count |
| Top contributors ranked by commits, with percentage insights |
| Fetches PR diffs and generates an AI summary with risk level |
| Finds beginner-friendly issues filtered by label — great for open source contributions |
How it works
You (in Claude Desktop)
↓
Claude AI
↓
MCP Server (this project)
↓
GitHub REST API + Groq AI
↓
Formatted response back to ClaudeWhen you ask Claude about a repo, it calls one of the tools registered in this server. The server fetches data from GitHub, optionally runs it through Groq for AI summaries, formats everything into clean markdown, and sends it back to Claude to show you.
Tech Stack
Runtime — Node.js + TypeScript
MCP SDK —
@modelcontextprotocol/sdk(connects to Claude Desktop)GitHub API — via
axioswith token authAI Summaries — Groq API (fast, free tier available)
Config —
dotenvfor environment variables
Project Structure
src/
├── server.ts # Entry point — wires up the MCP server
├── tools/
│ ├── registry.ts # Tool registry — all tools defined and dispatched here
│ ├── issues.ts # Open issues logic
│ ├── contributors.ts # Contributors logic
│ ├── pullRequest.ts # PR fetch + AI summary
│ └── goodFirstIssues.ts # Beginner issue finder
├── services/
│ ├── githubService.ts # Shared GitHub axios client
│ └── aiService.ts # Groq AI summarization
└── utils/
└── formatters.ts # Markdown formatters for all tool responsesGetting Started
1. Clone and install
git clone https://github.com/aviralkaushik412/github-mcp-server
cd github-mcp-server
npm install2. Set up environment variables
Create a .env file in the root:
GITHUB_TOKEN=your_github_personal_access_token
GROQ_API_KEY=your_groq_api_keyGet a GitHub token at github.com/settings/tokens — needs
reposcopeGet a free Groq key at console.groq.com
3. Connect to Claude Desktop
Open your Claude Desktop config file:
Mac:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Add this:
{
"mcpServers": {
"github-mcp-server": {
"command": "npx",
"args": ["ts-node", "/absolute/path/to/src/server.ts"]
}
}
}4. Restart Claude Desktop and start asking
"Get stats for torvalds/linux"
"Find good first issues in facebook/react"
"Summarize PR #1 for aviralkaushik412/SkillMirror"Screenshots
Repo Stats

PR Summary with AI

Current working

What I learned building this
This project taught me a lot about how AI models actually work with tools — not just answering questions from memory, but taking actions and fetching real-time data.
A few things that were genuinely tricky:
MCP servers communicate over stdout as a JSON stream — one stray
console.log()breaks everything silentlyClaude decides which tool to call based on the tool's
descriptionfield — so wording matters a lotStructuring responses as clean markdown makes Claude's output dramatically better
Coming Soon
explain_repository— AI-generated plain-English explanation of what any repo doesanalyze_pr_risk— flags high-risk PRs based on file count, diff size, and sensitive pathsReact dashboard frontend for non-Claude-Desktop users
Resume Bullet Points
If you're here from my resume, here's the one-liner version:
Built a production-ready Model Context Protocol (MCP) server in TypeScript that connects Claude AI to the GitHub REST API and Groq AI, enabling natural language queries over live repository data via 5 registered tools with structured error handling, formatted markdown responses, and a tool registry pattern.
Author
Aviral Kaushik github.com/aviralkaushik412
Built with Claude Desktop, TypeScript, and a lot of stderr debugging.
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