Introduction to FastMCP and Model Context Protocol

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is a revolutionary standardized way to provide context and tools to Large Language Models (LLMs). Often described as "the USB-C port for AI," MCP provides a uniform interface for connecting LLMs to external resources and functionality.

Think of MCP as a specialized API designed specifically for LLM interactions. MCP servers can:

• Expose data through Resources (similar to GET endpoints for loading information)
• Provide functionality through Tools (similar to POST endpoints for executing actions)
• Define interaction patterns through Prompts (reusable templates for LLM conversations)
• Manage connections securely and efficiently

Why FastMCP?

Building MCP servers from scratch involves significant boilerplate code - server setup, protocol handlers, content type management, and error handling. FastMCP eliminates this complexity by providing a high-level, Pythonic interface that lets you focus on building great functionality.

FastMCP 2.0 is the actively maintained version that goes far beyond basic protocol implementation. It offers:

🚀 Fast Development: High-level interface means less code and faster development
🍀 Simple API: Build MCP servers with minimal boilerplate
🐍 Pythonic Design: Feels natural to Python developers
🔍 Complete Platform: Comprehensive toolkit from development to production

FastMCP Features

Core Capabilities

• Easy Server Creation: Create MCP servers with just a few lines of code
• Decorator-Based Design: Simple decorators to convert functions into MCP tools
• Multiple Transport Support: STDIO, HTTP, and SSE transports
• Type Safety: Automatic schema generation from Python type hints
• Async Support: Full support for both sync and async functions

Advanced Features

• Server Composition: Mount multiple servers together
• Proxy Servers: Create intermediary servers for existing MCP services
• Authentication: Built-in security for production deployments
• OpenAPI Integration: Generate servers from existing REST APIs
• Client Libraries: Comprehensive client support for testing and integration

A Simple Example

Let's see how easy it is to create a basic MCP server with FastMCP:

from fastmcp import FastMCP

# Create a server instance
mcp = FastMCP("Demo Server 🚀")

@mcp.tool
def add_numbers(a: int, b: int) -> int:
    """Add two numbers together."""
    return a + b

@mcp.tool
def greet_user(name: str) -> str:
    """Greet a user by name."""
    return f"Hello, {name}! Welcome to FastMCP!"

if __name__ == "__main__":
    mcp.run()

That's it! This creates a fully functional MCP server with two tools that can be called by any MCP client.

Next Steps

In the following sections, we'll dive deeper into: - Setting up your FastMCP development environment - Creating sophisticated tools and resources - Building production-ready servers - Integrating with Claude Code and other MCP clients - Advanced patterns and best practices

FastMCP makes the powerful Model Context Protocol accessible to Python developers, enabling you to build sophisticated AI-powered applications with minimal effort.