MCP Server Sample

This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes. This code demonstrates how to build a functional MCP server that can integrate with various LLM clients.

MCP Server Example

This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes. This code demonstrates how to build a functional MCP server that can integrate with various LLM clients.

References:

• Model Context Protocol - Anthropic.
• MCP - Python.

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.

Key Benefits

• A growing list of pre-built integrations that your LLM can directly plug into
• Flexibility to switch between LLM providers and vendors
• Best practices for securing your data within your infrastructure

Architecture Overview

MCP follows a client-server architecture where a host application can connect to multiple servers:

• MCP Hosts: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP
• MCP Clients: Protocol clients that maintain 1:1 connections with servers
• MCP Servers: Lightweight programs that expose specific capabilities through the standardized Model Context Protocol
• Data Sources: Both local (files, databases) and remote services (APIs) that MCP servers can access

Core MCP Concepts

MCP servers can provide three main types of capabilities:

• Resources: File-like data that can be read by clients (like API responses or file contents)
• Tools: Functions that can be called by the LLM (with user approval)
• Prompts: Pre-written templates that help users accomplish specific tasks

System Requirements

• Python 3.10 or higher
• MCP SDK 1.2.0 or higher
• uv package manager

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Installation

Adding MCP to your python project

We recommend using uv to manage your Python projects.

If you haven't created a uv-managed project yet, create one:

uv init mcp-server-sample
cd mcp-server-sample

Then add MCP to your project dependencies:

uv add "mcp[cli]

Alternatively, for projects using pip for dependencies:

pip install "mcp[cli]"

Running the standalone MCP development tools

To run the mcp command with uv:

uv run mcp

Quickstart

Let's create a simple MCP server that exposes a calculator tool and some data:

# server.py
from mcp.server.fastmcp import FastMCP

# Create an MCP server
mcp = FastMCP("Demo")

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

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

You can install this server in Claude Desktop and interact with it right away by running:

mcp install server.py

Alternatively, you can test it with the MCP Inspector:

mcp dev server.py

Made with ❤️ by Antonio Scapellato

Resources:

• Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic

License

This project is licensed under the MIT License. See the LICENSE file for details.