mcpField
M
MCP Server for Deepseek Integration

MCP Server for Deepseek Integration

Local
github.com/vincentf305AI & Agents4Updated 91w ago
Repository

About MCP Server for Deepseek Integration

An MCP server that lets Claude Desktop use Deepseek models through a Deepseek API key. It can run in Docker or locally.

Key features

  1. 01Connect Claude Desktop to Deepseek
  2. 02Run in Docker or locally
  3. 03Configure access with an API key

Use cases

  1. 01Use Deepseek models from Claude Desktop
  2. 02Run the server in a Docker container

MCP support

Exposes Deepseek integration to MCP clients, with Claude Desktop shown as the client. The server can run in Docker or locally.

#mcp-server#deepseek#integration

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "deepseek": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "build"
      ]
    }
  }
}
Run commanddocker run -i --rm build

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocibuild

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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

Comments

Markdown supported

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.