By learning new concepts introduced in the AI world, you can always be a better developer, having a better understanding of what’s new and what technologies should you adapt. MCP introduced by Anthropic is one of these major new incoming concepts into the world of AI. This is a detailed guide on how to build a custom Model Context Protocol (MCP) server using Python.

Introduction

In this post, we’ll explore what the Model Context Protocol (MCP) is and how to build a custom MCP server using Python. If you’ve been hearing about MCP and wondering what it does or why it’s important, this guide is for you.

What is MCP?

MCP (Model Context Protocol) is an open standard developed by Anthropic that allows you to connect external tools, resources, and prompt templates to AI applications.

It’s often described as the USB-C port for AI, providing a standardized way to plug tools and context into models like Claude.

Why MCP Matters

• ✅ Port custom integrations (e.g., Slack, Google Drive) into AI apps.
• 🔁 Reuse toolsets across environments (VS Code, Cursor, WindSurf).
• 🌍 Tap into the open ecosystem of MCP-compatible servers and tools.

How MCP Works

MCP uses a client-server architecture:

• The client (e.g. Claude Desktop) sends requests.
• The server (your custom code) responds with tools, resources, or prompts.

Think of it like a shopping store:

• You (client) ask for a cloth.
• The salesperson (server) prepares and gives it to you.

MCP Client

• Embedded inside AI applications.
• Handles discovery of tools and resources.
• Manages execution (LLMs can’t do it themselves).
• Already implemented in apps like Claude Desktop.

As a user or developer, you typically don’t need to build the client — only the server.

MCP Server

The server is an independent module that:

• Listens for requests.
• Provides:
  • Prompts (e.g., resume writing templates)
  • Resources (static files, databases)
  • Tools (functions, APIs, scripts)

Transport Methods

• stdio for local development.
• HTTP + Server Sent Events (SSE) for cloud deployments.

Example: MCP Server with Python

Using Anthropic’s Python SDK, you can spin up a server that connects tools to Claude Desktop.

Steps:

1. Install uv – a Rust-based fast Python environment manager.
2. Use the SDK:
   • Define prompts via @mcp.prompt
   • Load resources via @mcp.resource
   • Execute tools via @mcp.tool

Example tools:

• Writing to Gmail.
• Accessing CSV contact lists.
• Reusing markdown templates.

Connecting to Claude Desktop

1. Install Claude Desktop.
2. Go to Settings > Developer > Edit Config.
3. Add the MCP server JSON config.
4. Restart Claude.

You’ll now see all the tools, resources, and prompts live inside Claude — ready to use!

Summary

MCP makes AI apps:

• More customizable 🚀
• More interoperable 🧩
• More powerful 💡

You define your own workflows and carry them between environments or apps — all with just a bit of Python and MCP.