MCP Server Playbook 2025

🚀 MCP Server Quick Start Guide: Building with Python

This guide provides a concise overview of the Anthropic's Model Context Protocol (MCP) and demonstrates how to build, test, integrate, and deploy an MCP server using the official MCP Python SDK.

✨ Features

• The MCP Python SDK offers tools for building MCP servers and clients, enabling seamless interaction between Large Language Models (LLMs) and external data sources or tools.
• The SDK adheres to the complete MCP specification, ensuring compatibility and standardization. GitHub Repository

📦 Installation

To integrate MCP into your Python project, it is recommended to use uv, a Python package manager:

uv add "mcp[cli]"

Alternatively, if you are using pip:

pip install mcp

💻 Usage Examples

Basic Usage

Let's create a simple MCP server that provides a calculator tool and a personalized greeting resource:

from mcp.server.fastmcp import FastMCP

# Initialize the MCP server
mcp = FastMCP("Example Server")

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

# Define the dynamic greeting resource
@mcp.resource("greeting://{name}")
def get_greeting(name: str) -> str:
    """Generate a personalized greeting."""
    return f"Hello, {name}!"

# Run the server
if __name__ == "__main__":
    mcp.run()

Advanced Usage

Testing the MCP Server

Use the MCP Inspector to test the server:

mcp dev server.py

This command launches the MCP Inspector, allowing you to interact with and verify the server's functionality.

Client Integration

Example: Integrating with an AI assistant (e.g., Claude Desktop):

mcp install server.py

This command installs the server into Claude Desktop, enabling the assistant to interact seamlessly with the MCP server.

🔧 Technical Details

When deploying an MCP server, consider the following aspects:

• Security: Implement authentication mechanisms such as API keys or OAuth to control access.
• Scalability: Use containerization tools like Docker to manage multi - environment deployments.
• Monitoring: Set up logging and monitoring to track server performance and diagnose issues promptly.