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:
Then add MCP to your project dependencies:
Alternatively, for projects using pip for dependencies:
Running the standalone MCP development tools To run the mcp command with uv:
Quickstart
Let's create a simple MCP server that exposes a calculator tool and some data:
You can install this server in Claude Desktop and interact with it right away by running:
Alternatively, you can test it with the MCP Inspector:
Made with ❤️ by Antonio Scapellato
License
This project is licensed under the MIT License. See the LICENSE file for details.
This server cannot be installed
An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.
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