# 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:
```bash
git clone https://github.com/tian1ll1/mcp-server-demo.git
cd mcp-server-demo
```
2. Create a virtual environment (recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. Start the MCP server:
```bash
python src/server.py
```
2. Run the example client:
```bash
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.
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/tian1ll1/mcp-server-demo'
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