MCP Connector

Connect Claude Desktop to Qwen Max language models

Qwen Max MCP Server lets Claude call Alibaba's Qwen-Max, Qwen-Plus, or Qwen-Turbo models for text generation via Dashscope.

Works with qwendashscopealibaba cloudclaude desktop

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Updated Jul 2025
Source checked Sep 10, 2026
Version 1.0.0

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Why it matters

Enable Claude Desktop to leverage Alibaba Cloud's Qwen family of language models (Max, Plus, Turbo) for text generation, code creation, and complex reasoning tasks through a Model Context Protocol server.

Outcomes

What it gets done

01

Generate text and code using Qwen-Max for complex multi-step tasks with 32K token context

02

Process large documents with Qwen-Turbo's 1M token context window at low cost

03

Balance performance and cost with Qwen-Plus for moderately complex tasks

04

Configure temperature and token parameters to control output creativity and length

Source

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Overview

Qwen_Max

Qwen Max MCP Server exposes Alibaba's Qwen-Max, Qwen-Plus, and Qwen-Turbo commercial models to Claude Desktop for text generation via the Dashscope API, with configurable max_tokens and temperature. Use it when Claude should delegate generation to a Qwen model for its context-window, speed, or cost tradeoffs; requires a Dashscope API key.

What it does

Qwen Max MCP Server is a Node.js/TypeScript MCP server that exposes Alibaba's Qwen commercial language models to Claude Desktop for text generation. Its single tool takes a prompt plus optional max_tokens and temperature parameters and returns generated text from the configured Qwen model, using the Dashscope API. By default it calls Qwen-Max; switching to Qwen-Plus or Qwen-Turbo is done by editing the model name in the server's src/index.ts source and rebuilding.

When to use - and when NOT to

Use it when Claude needs to delegate a generation task to a Qwen model instead of its own - useful for comparing outputs, working within Qwen's specific context-window and pricing tradeoffs, or when a task specifically calls for one of Alibaba's commercial models. Qwen-Max gives the best performance on complex, multi-step tasks with a 32,768-token context window; Qwen-Plus balances performance, speed, and cost with a 131,072-token window; Qwen-Turbo is fast and cheap with a 1,000,000-token window, suited to simple tasks. It requires a Dashscope API key and Node.js v18+; each model choice is compiled in rather than selected per-call, so switching models means changing the source and rebuilding.

Capabilities

Each model family has stable, latest, and dated-snapshot versions - for example qwen-max, qwen-max-latest, and qwen-max-2025-01-25, also called qwen-max-0125 or Qwen2.5-Max. Pricing per 1K tokens ranges from $0.0016 input / $0.0064 output for Qwen-Max down to $0.00005 input / $0.0002 output for Qwen-Turbo, each with a 1 million token free quota. The temperature parameter is documented with task-specific guidance: 0.0-0.3 for code generation, 0.3-0.5 for technical writing, 0.7 (the default) for general tasks, and 0.8-1.0 for creative writing. The server surfaces detailed error messages for API authentication failures, invalid parameters, rate limiting, network issues, exceeded token limits, and model availability problems.

How to install

Install via Smithery for Claude Desktop:

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

For manual installation, clone the repository, run npm install, then npm run build. Set a .env file or environment variable with DASHSCOPE_API_KEY=your-api-key-here, and register the server in Claude Desktop's config with a node command pointing at the built build/index.js, passing the same API key as an environment variable. Requires Node.js v18 or higher. Released under the MIT license.

Who it's for

Developers who want Claude to call Alibaba's Qwen-Max, Qwen-Plus, or Qwen-Turbo models directly for text generation, taking advantage of Qwen's context-window and pricing tradeoffs for a specific task.

Source README

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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:

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

Manual Installation

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

// 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.

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:
{
  "mcpServers": {
    "qwen_max": {
      "command": "node",
      "args": ["/path/to/Qwen_Max/build/index.js"],
      "env": {
        "DASHSCOPE_API_KEY": "your-api-key-here"
      }
    }
  }
}

Development

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

// Example tool call
{
  "name": "qwen_max",
  "arguments": {
    "prompt": "Your prompt here",
    "max_tokens": 8192,
    "temperature": 0.7
  }
}

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

FAQ

Common questions

Discussion

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