MCP (Model Context Protocol) Explained — The Universal AI Tool Standard

Model Context Protocol (MCP) is an open standard by Anthropic that standardizes how AI models connect to external tools. Think of it as USB for AI.

The Problem MCP Solves

Before MCP, every AI tool integration was custom code. MCP provides one standard protocol for all tools.

Building an MCP Server

from mcp.server import Server
import json

server = Server('my-tools')

@server.tool()
async def search_database(query: str) -> str:
    """Search the product database."""
    results = db.search(query)
    return json.dumps(results)

@server.tool()
async def send_email(to: str, subject: str, body: str) -> str:
    """Send an email."""
    send(to, subject, body)
    return f'Email sent to {to}'

if __name__ == '__main__':
    server.run()

Why MCP Matters

• Reusability — Build once, use with any MCP-compatible AI
• Ecosystem — Growing library of pre-built MCP servers
• Security — Built-in permission model and sandboxing
• Composability — Mix tools from different servers

MCP Architecture

AI Model (Client) <--MCP Protocol--> MCP Server (Tools)
                                           |
                                    Database / API / Files

Using MCP with Claude Desktop

Configure in your Claude Desktop settings:

{
  "mcpServers": {
    "my-tools": {
      "command": "python",
      "args": ["my_mcp_server.py"]
    }
  }
}

Learn More

Full lesson on Claude + MCP in our AI agent course:

Start free (no signup needed): learnhowtobuildaiagents.com