What is MCP (Model Context Protocol) for Developers?

If you use AI coding tools like Claude Code, Cursor, or Windsurf, you've probably heard of MCP. But what is it, and why should you care?

MCP in plain English

The Model Context Protocol (MCP) is an open standard that lets AI assistants connect to external tools and data sources. Think of it as a USB port for AI — a universal way to plug in capabilities.

Without MCP, your AI assistant only knows what's in its training data and what you paste into the chat. With MCP, it can reach out to real systems — databases, APIs, monitoring tools — and pull in live data.

How MCP works

MCP uses a client-server architecture:

• MCP Client — your AI tool (Claude Code, Cursor, etc.)
• MCP Server — a service that exposes tools and data

The server advertises what tools it has (like "list recordings" or "get errors"), and the AI client can call those tools when relevant to your conversation.

Real-world example: debugging with AI

Say you're working on a bug fix and you have a screen recording of the bug. Without MCP, you'd manually look at the recording, copy error messages, and paste them into your AI assistant.

With an MCP integration, you can simply ask your AI assistant: "What errors happened in my last recording?" — and it fetches the real data directly from your recording tool.

Setting up an MCP server

Most MCP servers are configured through a simple JSON file. Here's what a typical setup looks like:

{
  "mcpServers": {
    "my-tool": {
      "type": "http",
      "url": "https://api.example.com/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_TOKEN"
      }
    }
  }
}

Drop this in your project's .mcp.json file, restart your AI tool, and you're connected.

What tools support MCP?

MCP is supported by a growing list of AI coding tools:

• Claude Code — Anthropic's CLI tool
• Cursor — AI-native code editor
• Windsurf — Codeium's AI IDE
• VS Code — via GitHub Copilot

Building your own MCP server

If you have an API that developers interact with, consider building an MCP server. The Model Context Protocol specification is open and well-documented, and SDKs are available for TypeScript, Python, and other languages.

The takeaway

MCP bridges the gap between AI assistants and real-world developer tools. Instead of copy-pasting context into chat windows, you can let your AI pull in exactly the data it needs. It's a small configuration change that makes AI coding tools significantly more useful.