Introduction to Model Context Protocol (MCP)

What is MCP?

The Model Context Protocol (MCP) is an open standard that defines how applications interact with large language models (LLMs). It allows applications to provide context for LLMs in a standardized way, separating the concerns of providing context from the actual LLM interaction.

MCP lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but specifically designed for LLM interactions.

MCP allows models to:

  1. Request information from the application through resources

  2. Take actions through function calling with tools

  3. Generate structured prompts for specific use cases

About FastMCP

FastMCP is a high-level, Pythonic interface for building MCP servers. Originally developed as a standalone project, it has now been integrated into the official MCP Python SDK. FastMCP provides a developer-friendly way to create MCP servers with minimal boilerplate.

Key features of FastMCP:

  • Simple decorators for defining resources, tools, and prompts

  • Automatic type handling for Python objects, Pydantic models, and images

  • Built-in development tools for testing and debugging

  • Claude Desktop integration for seamless deployment

Here’s a minimal example:

from mcp.server.fastmcp import FastMCP

mcp = FastMCP("Demo πŸš€")

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

Core Concepts

MCP defines several core primitives:

Primitive

Who Controls

Description

Resources

Application

Contextual data managed by the client application. Models can request resources to get information (files, API data, etc.).

Tools

Model

Functions exposed to the LLM to take actions. Models can call tools to perform computations or produce side effects.

Prompts

User

Interactive templates invoked by user choice. Users choose prompts from options provided by the application.

Images

Application

Visual data that can be shared with or generated by models.

Context

Application

Access to MCP capabilities within tools and resources.

Benefits of MCP

  • Reliability: Models can request exactly what they need instead of hallucinating.

  • Capability: Models can take actions in the real world through well-defined interfaces.

  • Customization: Applications can guide model behavior through structured prompts.

  • Interoperability: A standard protocol works across different models and applications.

  • Type Safety: Strong typing for context and data across the protocol.

  • Pythonic: With FastMCP, build servers using intuitive Python patterns.

  • Development Simplicity: Streamlined testing and debugging with built-in tools.

Running MCP Servers

There are three main ways to use your MCP server:

  1. Development Mode: Test with the MCP Inspector web interface (mcp dev server.py)

  2. Claude Desktop Integration: Add to Claude Desktop for regular use (mcp install server.py)

  3. Direct Execution: Run standalone for custom deployments (python server.py)

About This Documentation

This documentation will guide you through:

  1. Getting started with the MCP Python SDK

  2. Building MCP servers to expose resources, tools, and prompts

  3. Creating MCP clients to connect to servers

  4. Exploring advanced topics and best practices

For the full specification, visit the official MCP documentation or the MCP specification.