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mcp-server-deepseek

MCP server enables Claude Desktop to use Deepseek models running in Docker, facilitating local AI integration.

Introduction

MCP Server for Deepseek Integration

This repository contains a Model Control Protocol (MCP) server implementation that allows Claude Desktop to use Deepseek models running in Docker.

Prerequisites
  • Docker
  • Python 3.11 or later
  • A Deepseek API key
  • Claude Desktop
Installation
  1. Clone the repository:
git clone https://github.com/vincentf305/mcp-server-deepseek.git
cd mcp-server-deepseek
  1. Install dependencies:
pip install -r requirements.txt
Setup Environment Variables

Create a .env file in the root directory of the project and add the following environment variable:

DEEPSEEK_API_KEY=your_api_key_here

Make sure to replace your_api_key_here with your actual Deepseek API key.

Running the Server
Using Docker
  1. Build the Docker image:
docker build -t mcp_server_deepseek .
  1. Run the container:
docker run -d \
  --name mcp-server-deepseek \
  -p 8765:8765 \
  -e DEEPSEEK_API_KEY=your_api_key_here \
  mcp-server-deepseek
Running Locally
python -m mcp_server_deepseek.server
Usage with Claude Desktop
  1. Ensure you have a Deepseek API key
  2. Add the following to your Claude Desktop configuration (claude_desktop_config.json):
{
  "mcpServers": {
    "deepseek-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DEEPSEEK_API_KEY",
        "mcp_server_deepseek"
      ],
      "env": {
        "DEEPSEEK_API_KEY": "your_api_key_here"
      }
    }
  }
}
  1. Restart Claude Desktop to load the new configuration
Contributing
  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Create a Pull Request
License

MIT License - see the LICENSE file for details

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