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MCP-server-Deepseek_R1

用于Deepseek R1语言模型的Node.js/TypeScript实现的模型上下文协议服务器,针对具有大上下文窗口的推理任务进行了优化,并与Claude Desktop完全集成。

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README

Deepseek R1 MCP Server

A Model Context Protocol (MCP) server implementation for the Deepseek R1 language model. Deepseek R1 is a powerful language model optimized for reasoning tasks with a context window of 8192 tokens.

Why Node.js? This implementation uses Node.js/TypeScript as it provides the most stable integration with MCP servers. The Node.js SDK offers better type safety, error handling, and compatibility with Claude Desktop.

Deepseek R1 Server MCP server

Quick Start

Installing manually

# Clone and install
git clone https://github.com/66julienmartin/MCP-server-Deepseek_R1.git
cd deepseek-r1-mcp
npm install

# Set up environment
cp .env.example .env  # Then add your API key

# Build and run
npm run build

Prerequisites

  • Node.js (v18 or higher)
  • npm
  • Claude Desktop
  • Deepseek API key

Model Selection

By default, this server uses the deepseek-R1 model. If you want to use DeepSeek-V3 instead, modify the model name in src/index.ts:

// For DeepSeek-R1 (default)
model: "deepseek-reasoner"

// For DeepSeek-V3
model: "deepseek-chat"

Project Structure

deepseek-r1-mcp/
├── src/
│   ├── index.ts             # Main server implementation
├── build/                   # Compiled files
│   ├── index.js
├── LICENSE
├── README.md
├── package.json
├── package-lock.json
└── tsconfig.json

Configuration

  1. Create a .env file:
DEEPSEEK_API_KEY=your-api-key-here
  1. Update Claude Desktop configuration:
{
  "mcpServers": {
    "deepseek_r1": {
      "command": "node",
      "args": ["/path/to/deepseek-r1-mcp/build/index.js"],
      "env": {
        "DEEPSEEK_API_KEY": "your-api-key"
      }
    }
  }
}

Development

npm run dev     # Watch mode
npm run build   # Build for production

Features

  • Advanced text generation with Deepseek R1 (8192 token context window)
  • Configurable parameters (max_tokens, temperature)
  • Robust error handling with detailed error messages
  • Full MCP protocol support
  • Claude Desktop integration
  • Support for both DeepSeek-R1 and DeepSeek-V3 models

API Usage

{
  "name": "deepseek_r1",
  "arguments": {
    "prompt": "Your prompt here",
    "max_tokens": 8192,    // Maximum tokens to generate
    "temperature": 0.2     // Controls randomness
  }
}

The Temperature Parameter

The default value of temperature is 0.2.

Deepseek recommends setting the temperature according to your specific use case:

| USE CASE | TEMPERATURE | EXAMPLE | |----------|-------------|---------| | Coding / Math | 0.0 | Code generation, mathematical calculations | | Data Cleaning / Data Analysis | 1.0 | Data processing tasks | | General Conversation | 1.3 | Chat and dialogue | | Translation | 1.3 | Language translation | | Creative Writing / Poetry | 1.5 | Story writing, poetry generation |

Error Handling

The server provides detailed error messages for common issues:

  • API authentication errors
  • Invalid parameters
  • Rate limiting
  • Network issues

Contributing

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

License

MIT

help

Runtime guide

cloud

Hosted runtime

Hosted servers run from a provider-managed environment. You usually connect the MCP client to the hosted endpoint or follow the provider's authorization flow, without keeping a local process alive

  1. Open provider connection page
  2. Authorize or copy endpoint
  3. Connect from your MCP client
terminal

Local runtime / other methods

Local servers run on your own machine or infrastructure. You normally copy the server_config into your MCP client, install the required package, and provide env variables from env_schema when needed

  1. Copy server_config
  2. Install required package
  3. Fill env variables and restart client