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Qwen_Max

Qwen_Max

by 66julienmartin
GitHub

A Model Context Protocol (MCP) server implementation for the Qwen models.

model
max
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Qwen Max MCP Server

A Model Context Protocol (MCP) server implementation for the Qwen Max language model.

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Qwen Max Server MCP server

Why Node.js? This implementation uses Node.js/TypeScript as it currently provides the most stable and reliable integration with MCP servers compared to other languages like Python. The Node.js SDK for MCP offers better type safety, error handling, and compatibility with Claude Desktop.

Prerequisites

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

Installation

Installing via Smithery

To install Qwen Max MCP Server for Claude Desktop automatically via Smithery:

1npx -y @smithery/cli install @66julienmartin/mcp-server-qwen_max --client claude

Manual Installation

1git clone https://github.com/66julienmartin/mcp-server-qwen-max.git
2cd Qwen_Max
3npm install

Model Selection

By default, this server uses the Qwen-Max model. The Qwen series offers several commercial models with different capabilities:

Qwen-Max

Provides the best inference performance, especially for complex and multi-step tasks.

Context window: 32,768 tokens

  • Max input: 30,720 tokens
  • Max output: 8,192 tokens
  • Pricing: $0.0016/1K tokens (input), $0.0064/1K tokens (output)
  • Free quota: 1 million tokens

Available versions:

  • qwen-max (Stable)
  • qwen-max-latest (Latest)
  • qwen-max-2025-01-25 (Snapshot, also known as qwen-max-0125 or Qwen2.5-Max)

Qwen-Plus

Balanced combination of performance, speed, and cost, ideal for moderately complex tasks.

Context window: 131,072 tokens

  • Max input: 129,024 tokens
  • Max output: 8,192 tokens
  • Pricing: $0.0004/1K tokens (input), $0.0012/1K tokens (output)
  • Free quota: 1 million tokens

Available versions:

  • qwen-plus (Stable)
  • qwen-plus-latest (Latest)
  • qwen-plus-2025-01-25 (Snapshot, also known as qwen-plus-0125)

Qwen-Turbo

Fast speed and low cost, suitable for simple tasks.

  • Context window: 1,000,000 tokens
  • Max input: 1,000,000 tokens
  • Max output: 8,192 tokens
  • Pricing: $0.00005/1K tokens (input), $0.0002/1K tokens (output)
  • Free quota: 1 million tokens

Available versions:

  • qwen-turbo (Stable)
  • qwen-turbo-latest (Latest)
  • qwen-turbo-2024-11-01 (Snapshot, also known as qwen-turbo-1101)

To modify the model, update the model name in src/index.ts:

1// For Qwen-Max (default)
2model: "qwen-max"
3
4// For Qwen-Plus
5model: "qwen-plus"
6
7// For Qwen-Turbo
8model: "qwen-turbo"

For more detailed information about available models, visit the Alibaba Cloud Model Documentation https://www.alibabacloud.com/help/en/model-studio/getting-started/models?spm=a3c0i.23458820.2359477120.1.446c7d3f9LT0FY.

Project Structure

qwen-max-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 in the project root:
DASHSCOPE_API_KEY=your-api-key-here
  1. Update Claude Desktop configuration:
1{
2  "mcpServers": {
3    "qwen_max": {
4      "command": "node",
5      "args": ["/path/to/Qwen_Max/build/index.js"],
6      "env": {
7        "DASHSCOPE_API_KEY": "your-api-key-here"
8      }
9    }
10  }
11}

Development

1npm run dev     # Watch mode
2npm run build   # Build
3npm run start   # Start server

Features

  • Text generation with Qwen models
  • Configurable parameters (max_tokens, temperature)
  • Error handling
  • MCP protocol support
  • Claude Desktop integration
  • Support for all Qwen commercial models (Max, Plus, Turbo)
  • Extensive token context windows

API Usage

1// Example tool call
2{
3  "name": "qwen_max",
4  "arguments": {
5    "prompt": "Your prompt here",
6    "max_tokens": 8192,
7    "temperature": 0.7
8  }
9}

The Temperature Parameter

The temperature parameter controls the randomness of the model's output:

Lower values (0.0-0.7): More focused and deterministic outputs Higher values (0.7-1.0): More creative and varied outputs

Recommended temperature settings by task:

Code generation: 0.0-0.3 Technical writing: 0.3-0.5 General tasks: 0.7 (default) Creative writing: 0.8-1.0

Error Handling

The server provides detailed error messages for common issues:

API authentication errors Invalid parameters Rate limiting Network issues Token limit exceeded Model availability issues

Contributing

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

License

MIT