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CloudBase AI Toolkit + Qwen Code

🚀 Qwen Code + CloudBase = Full-stack application from idea to launch in minutes.

GitHub Stars Open Source License

💡 Why choose Qwen Code + CloudBase AI Toolkit?
Qwen Code is an open-source modification of the Gemini CLI command-line AI programming tool, specifically optimized for the Qwen3-Coder model, supporting a large context window, rich local AI workflows, and the MCP protocol. It is suitable for command-line enthusiasts, automated script development, and rapid prototyping.

✨ Core Advantages​

🎯 Development Efficiency⚡ Deployment Speed🛡️ Stability and Reliability
AI automatically generates code and architecture
Built-in best practice rules for cloud development
Intelligent error fixing and optimization		One-click deployment to Tencent Cloud development
Domestic CDN accelerated access
Serverless architecture with no Ops required		Platform verified by 3.3 million developers
Enterprise-grade security and stability
Comprehensive monitoring and logging system

🚀 5-Minute Quick Start​

Select pre-configured project templates, ready to use out-of-the-box:

Method 2: Integrate with existing projects​

If you already have a project, you can integrate in just 3 steps:

# 1. Configure MCP (See detailed steps below for specific configuration)
# 2. Download AI Rules
# 3. Start Using

After configuration is complete, tell the AI: "Log in to CloudBase" to begin!

Step 3: Enable AI Rules​

You can place .qwen/QWEN.md in the project root directory, maintaining the same content structure as CLAUDE.md/GEMINI.md.

If it is an existing project, tell the AI:

Download CloudBase AI rules in the current project

If you only want to download configuration files related to Qwen Code to avoid cluttering your project files, you can specify the IDE type:

Download CloudBase AI rules in the current project, containing only Qwen Code configuration

🔧 Detailed Configuration Guide​

Step 1: Install Qwen Code​

Requires Node.js 20+. Recommended for global installation:

npm install -g @qwen-code/qwen-code

Or run directly:

npx @qwen-code/qwen-code

Step 2: Configure CloudBase MCP​

Create .qwen/settings.json in the project root directory or home directory:

{
  "mcpServers": {
    "cloudbase": {
      "command": "npx",
      "args": [
        "npm-global-exec@latest",
        "@cloudbase/cloudbase-mcp@latest"
      ],
      "env": {
        "INTEGRATION_IDE": "Qwen"
      }
    }
  }
}

Step 4: Start Development​

Under the Qwen Code command line, converse with the AI:

Log in to CloudBase

🎯 Get Started​

After configuration is complete, tell the AI:

Log in to CloudBase

Then you can start development, for example:

Create an online voting system that supports creating polls, participating in voting, and result statistics, using cloud database for storage, and finally deploy it.

🛠️ Troubleshooting​

Frequently Asked Questions​

Q: MCP connection failed? A:

  1. Check if the format of the .qwen/settings.json configuration file is correct
  2. Restart Qwen Code
  3. Confirm that the network connection is working properly

Q: Does the AI-generated code not meet expectations? A:

  1. Clearly specify the technology stack and framework requirements
  2. Use project templates to ensure specification consistency
  3. Provide more detailed requirement descriptions

For more questions, refer to: Complete FAQ

📚 Related Resources​

💬 Technical Discussions​

WeChat Technical Exchange Group​

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🚀 Get started with Qwen Code + CloudBase AI Toolkit immediately

Get Started | View Templates | GitHub Repository