GitHub Insights MCP Server

A small server that lets an AI assistant look up and analyze GitHub repositories.

It's built with the Model Context Protocol (MCP). MCP is a standard way to give an AI access to outside tools and data. You build the server once, and any MCP-compatible app (like Claude Desktop or Cursor) can use it.

What it can do

Look up a repo — get a repository's stars, forks, language, description, and open issues.

Search repos — search GitHub by keyword and get back the top results.

Read a README — pull any repository's README so the AI can read it.

Analyze a repo — a ready-made prompt that tells the AI to gather the repo's stats and README and give a clear verdict on whether the project is healthy and worth using.

Related MCP server: GitHub MCP Server

Built with

• TypeScript

• The MCP TypeScript SDK

• Zod (for checking inputs)

• The GitHub API (for live data)

• Node.js

How to run it

You'll need Node.js 18 or newer.

git clone https://github.com/YOUR_USERNAME/github-insights-mcp.git
cd git-mcp
npm install
npm run build

Try it out

The MCP Inspector is a simple tool for testing the server in your browser:

npm run inspect

Open the link it prints, click Connect, and try:

• Tools — look up facebook / react

• Resources — read repo://facebook/react/readme

• Prompts — run analyze_repo and see the instruction it creates

Use it with Claude Desktop

Add this to your Claude Desktop config file:

{
  "mcpServers": {
    "github-insights": {
      "command": "node",
      "args": ["/full/path/to/github-insights-mcp/dist/index.js"]
    }
  }
}

Restart Claude Desktop and the tools will be ready to use.

What I learned

Building this taught me how MCP actually works:

• How the client and server talk to each other, and why keeping them separate is useful

• The three things an MCP server can offer — tools (actions), resources (data to read), and prompts (ready-made instructions)

• How to connect real API calls, handle errors, and check inputs

• How one prompt can tie the tools and resources together into a single task

• END