AlibabaCloud DataWorks MCP Server

What does “AlibabaCloud DataWorks” MCP Server do?

The AlibabaCloud DataWorks MCP Server is a Model Context Protocol (MCP) server that enables AI agents and assistants to interact seamlessly with the DataWorks Open API from Alibaba Cloud. By providing a standardized interface to the Aliyun Open API, this server allows AI to manage and operate on cloud resources, such as orchestrating data pipelines, querying data assets, and automating cloud workflows. Its primary purpose is to bridge AI assistants with external cloud services, enabling tasks like resource management, file operations, and workflow execution within the DataWorks ecosystem. This enhances developer workflows by making cloud automation and resource management accessible through standardized, LLM-driven tools.

List of Prompts

No specific prompt templates are described in the documentation or code available.

Ready to grow your business?

Start your free trial today and see results within days.

Request demo Log in

List of Resources

No explicit MCP resource definitions are provided or listed in the available documentation or repository files.

List of Tools

• The server provides tools to manage DataWorks resources via the Open API. The following are referenced in the documentation (via environment variables or configuration):
  • ListProjects: Tool to list all projects within DataWorks.
  • Tools can be filtered by TOOL_CATEGORIES and TOOL_NAMES, suggesting the server exposes multiple DataWorks operation tools, but only ListProjects is explicitly mentioned.

Join our newsletter

Get latest tips, trends, and deals for free.

Email address

Subscribe

Use Cases of this MCP Server

• Cloud Resource Management: Enables developers to manage DataWorks resources (such as projects, workflows, and data assets) programmatically via AI assistants.
• Automated Data Operations: Facilitates automation of data pipeline operations, allowing AI agents to schedule, monitor, and manage ETL tasks.
• Integration with LLM Development Tools: Can be integrated into AI-powered development environments to enhance workflows with real-time cloud data and resource insights.
• Secure API Interaction: Ensures that sensitive access keys are managed via environment variables, supporting secure operations on Alibaba Cloud infrastructure.

How to set it up

Windsurf

1. Ensure you have Node.js (v16+) installed.
2. Install the package globally:
   npm install -g alibabacloud-dataworks-mcp-server
3. Open the Windsurf configuration file.
4. Add the MCP Server configuration under the mcpServers object:

   {
     "mcpServers": {
       "alibabacloud-dataworks-mcp-server": {
         "command": "npx",
         "args": ["alibabacloud-dataworks-mcp-server"],
         "env": {
           "REGION": "your_dataworks_open_api_region_id_here",
           "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
           "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret"
         }
       }
     }
   }
   

5. Save the configuration and restart Windsurf to apply changes.
6. Verify that the MCP server is running and available within the platform.

Claude

1. Install Node.js (v16+) and the MCP Server package:
   npm install -g alibabacloud-dataworks-mcp-server
2. Locate Claude’s configuration file for MCP servers.
3. Add the server entry as follows:

   {
     "mcpServers": {
       "alibabacloud-dataworks-mcp-server": {
         "command": "npx",
         "args": ["alibabacloud-dataworks-mcp-server"],
         "env": {
           "REGION": "your_dataworks_open_api_region_id_here",
           "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
           "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret"
         }
       }
     }
   }
   

4. Save and restart Claude.
5. Confirm the server is recognized and operational.

Cursor

1. Confirm Node.js (v16+) is installed.
2. Install globally:
   npm install -g alibabacloud-dataworks-mcp-server
3. Open Cursor’s MCP configuration.
4. Add the following JSON block:

   {
     "mcpServers": {
       "alibabacloud-dataworks-mcp-server": {
         "command": "npx",
         "args": ["alibabacloud-dataworks-mcp-server"],
         "env": {
           "REGION": "your_dataworks_open_api_region_id_here",
           "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
           "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret"
         }
       }
     }
   }
   

5. Save and restart Cursor.
6. Check for successful registration of the server.

Cline

1. Install Node.js (v16+) and the MCP server package:
   npm install -g alibabacloud-dataworks-mcp-server
2. Edit the Cline MCP server configuration.
3. Insert the following configuration:

   {
     "mcpServers": {
       "alibabacloud-dataworks-mcp-server": {
         "command": "npx",
         "args": ["alibabacloud-dataworks-mcp-server"],
         "env": {
           "REGION": "your_dataworks_open_api_region_id_here",
           "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
           "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret"
         }
       }
     }
   }
   

4. Save the file and restart Cline.
5. Verify operation via the platform interface.

Securing API Keys using Environment Variables

Always store sensitive credentials in environment variables. Here’s an example configuration:

{
  "mcpServers": {
    "alibabacloud-dataworks-mcp-server": {
      "command": "npx",
      "args": ["alibabacloud-dataworks-mcp-server"],
      "env": {
        "REGION": "your_dataworks_open_api_region_id_here",
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "${ALIBABA_CLOUD_ACCESS_KEY_ID}",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "${ALIBABA_CLOUD_ACCESS_KEY_SECRET}"
      }
    }
  }
}

Replace ${ALIBABA_CLOUD_ACCESS_KEY_ID} and ${ALIBABA_CLOUD_ACCESS_KEY_SECRET} with your actual environment variable names.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "alibabacloud-dataworks-mcp-server": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “alibabacloud-dataworks-mcp-server” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

Based on the above two tables, the AlibabaCloud DataWorks MCP server is solid in setup documentation, security, and tool exposure, but lacks details on prompts, resources, and advanced MCP features. The technical foundation seems strong for developers needing DataWorks integration, but some MCP-specific features are under-documented.

MCP Score

Rating:
I would rate this MCP implementation a 6/10. It is well-structured for its core purpose and security, but lacks comprehensive documentation for MCP-specific features like prompts, resources, roots, and sampling support. This limits its clarity for integration in broader MCP-enabled platforms.