I Built a Production MCP Server Kit — Here's What I Learned

Every MCP starter on GitHub is a hello-world. I needed production features.

I spent the last few months building MCP servers for real projects — integrating with Cursor, Claude Desktop, VS Code — and every time I started from an open-source template, I'd spend days bolting on the same stuff: auth, rate limiting, deployment configs, actual useful tools.

So I built the starter kit I wished existed. Here's what went into it and the decisions I made along the way.

The Problem Nobody Talks About

MCP (Model Context Protocol) is everywhere right now. Cursor uses it. Claude Desktop uses it. VS Code Copilot is adopting it. It's becoming the standard way AI agents talk to external tools.

But go look at the starter templates on GitHub. They all look like this:

server.tool("hello", "Says hello", {}, () => ({

  content: [{ type: "text", text: "Hello, world!" }],

}));

Cool. Now what?

You need auth because you're exposing this over the network. You need rate limiting because AI clients will hammer your server in a loop. You need actual tools that do real things — query databases, call APIs, read files. You need deployment configs because "just run it locally" doesn't work for teams.

Every single time, you copy a template and spend 2-3 days adding the stuff that should've been there from the start.

I got tired of that loop.

What I Built

The MCP Server Starter Kit is a production-ready TypeScript template with everything you need to ship a real MCP server. Not a toy. Not a demo. A starting point for actual projects.

Here's what's in the box:

• 
  5 production tools — Database queries, REST API integration, file system operations, web scraper, and a sandboxed code runner


• 
  Auth middleware — API key and JWT validation, pluggable for your own auth provider


• 
  Rate limiting — Per-client rate limiting so runaway AI agents don't melt your server


• 
  Dual transport — stdio for local development, SSE for remote/team usage


• 
  AWS CDK deployment — One-command deploy to Lambda + API Gateway


• 
  Docker support — Containerized for any environment


• 
  Full test suite — Unit and integration tests out of the box

The architecture looks like this:

— open source on GitHub. It's a clean minimal starter with stdio transport and a single example tool. Good for learning MCP, building simple local tools, or just understanding the protocol. Star it, fork it, ship something.

🚀 Pro Kit ($49) — — Full AI SaaS platform on AWS