MCP Server Sample

MIT License
1

Integrations

  • References the MCP SDK available through PyPI, which is used to implement the server's functionality.

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:

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

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

License

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

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security - not tested
A
license - permissive license
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quality - not tested

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.

  1. MCP Server Example
    1. What is MCP?
    2. Architecture Overview
    3. Core MCP Concepts
    4. System Requirements
    5. License

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