Model Context Protocol (MCP) Server
LocalAbout Model Context Protocol (MCP) Server
A Python proof-of-concept MCP server for learning the protocol’s core concepts. It demonstrates WebSocket communication, message validation, and context management with FastAPI and Pydantic.
Key features
- 01WebSocket communication
- 02MCP message handling with Pydantic
- 03Model context management
- 04Asynchronous request handling
Use cases
- 01Learning basic MCP server implementation
- 02Testing MCP client-server interactions
MCP support
Implements an MCP server that handles protocol messages and manages model context for connected clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEModel Context Protocol (MCP) Server
A basic implementation of a Model Context Protocol server for educational purposes. This server demonstrates the core concepts of MCP and how to implement them in practice using Python.
Features
- WebSocket-based communication using FastAPI and WebSockets
- Basic MCP message handling with Pydantic models
- Support for model context management
- Simple client-server interaction
- Async/await support for better performance
Getting Started
- Create a virtual environment (recommended):
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Start the development server:
python -m src.server
- Run the example client:
python examples/basic_usage.py
Project Structure
src/
├── server.py # Main server implementation
├── types/ # TypeScript type definitions
│ └── mcp.py # MCP protocol types using Pydantic
└── examples/ # Example implementations
└── basic_usage.py # Basic client example
MCP Protocol Overview
The Model Context Protocol (MCP) is a communication protocol designed for AI model interactions. This implementation includes:
- Message format handling using Pydantic models
- Context management
- Basic protocol operations
- Async/await support for better performance
Key Differences from TypeScript Version
- Uses FastAPI instead of Express
- Implements async/await for better performance
- Uses Pydantic for data validation and serialization
- More Pythonic code structure and patterns MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.