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MCP Server Demo

by tian1ll1

MCP Server Demo

This project demonstrates the implementation of a Model Context Protocol (MCP) server. MCP is a protocol designed to facilitate communication between AI models and external tools/services while maintaining context awareness.

Features

  • Basic MCP server implementation
  • Example tool integrations
  • Context management demonstration
  • WebSocket-based real-time communication
  • Simple client example

Project Structure

mcp-server-demo/ ├── src/ │ ├── server.py # Main MCP server implementation │ ├── tools/ # Tool implementations │ │ ├── __init__.py │ │ └── basic_tools.py │ ├── context/ # Context management │ │ ├── __init__.py │ │ └── manager.py │ └── utils/ # Utility functions │ ├── __init__.py │ └── helpers.py ├── examples/ # Example usage │ ├── client.py │ └── tools_demo.py ├── tests/ # Test cases │ └── test_server.py ├── requirements.txt # Project dependencies └── README.md # This file

Installation

  1. Clone the repository:
git clone https://github.com/tian1ll1/mcp-server-demo.git cd mcp-server-demo
  1. Create a virtual environment (recommended):
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt

Usage

  1. Start the MCP server:
python src/server.py
  1. Run the example client:
python examples/client.py

How It Works

The MCP server implements the following key components:

  1. Context Management: Maintains conversation history and relevant context for each session.
  2. Tool Registry: Manages available tools and their specifications.
  3. Message Processing: Handles incoming messages and routes them to appropriate tools.
  4. WebSocket Server: Provides real-time communication with clients.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

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security - not tested
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license - not found
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quality - not tested

A demonstration implementation of the Model Context Protocol server that facilitates communication between AI models and external tools while maintaining context awareness.

  1. Features
    1. Project Structure
      1. Installation
        1. Usage
          1. How It Works
            1. Contributing
              1. License

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