MCP server for Qwen Max model
A Model Context Protocol (MCP) server implementation for the Qwen Max language model.
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.
To install Qwen Max MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @66julienmartin/mcp-server-qwen_max --client claude
git clone https://github.com/66julienmartin/mcp-server-qwen-max.git
cd Qwen_Max
npm install
By default, this server uses the Qwen-Max model. The Qwen series offers several commercial models with different capabilities:
Provides the best inference performance, especially for complex and multi-step tasks.
Context window: 32,768 tokens
Available versions:
Balanced combination of performance, speed, and cost, ideal for moderately complex tasks.
Context window: 131,072 tokens
Available versions:
Fast speed and low cost, suitable for simple tasks.
Available versions:
To modify the model, update the model name in src/index.ts:
// For Qwen-Max (default)
model: "qwen-max"
// For Qwen-Plus
model: "qwen-plus"
// For Qwen-Turbo
model: "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.
qwen-max-mcp/
├── src/
│ ├── index.ts # Main server implementation
├── build/ # Compiled files
│ ├── index.js
├── LICENSE
├── README.md
├── package.json
├── package-lock.json
└── tsconfig.json
.env file in the project root:DASHSCOPE_API_KEY=your-api-key-here
{
"mcpServers": {
"qwen_max": {
"command": "node",
"args": ["/path/to/Qwen_Max/build/index.js"],
"env": {
"DASHSCOPE_API_KEY": "your-api-key-here"
}
}
}
}
npm run dev # Watch mode
npm run build # Build
npm run start # Start server
// Example tool call
{
"name": "qwen_max",
"arguments": {
"prompt": "Your prompt here",
"max_tokens": 8192,
"temperature": 0.7
}
}
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
The server provides detailed error messages for common issues:
API authentication errors Invalid parameters Rate limiting Network issues Token limit exceeded Model availability issues
Contributions are welcome! Please feel free to submit a Pull Request.
MIT
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