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DataWorks

Organization
aliyun

A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Aliyun Open API and enables AI agents to perform cloud resources operations seamlessly.

Publisheraliyun
Repositoryalibabacloud-dataworks-mcp-server
LanguageTypeScript
Forks
15
Stars
38
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    DataWorks exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    38 stars and 15 forks from the linked repository.

MseeP.ai Security Assessment Badge

DataWorks MCP Server

A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Aliyun Open API and enables AI agents to perform cloud resources operations seamlessly.

Overview

This MCP server:

  • Interact with DataWorks Open API
  • Manage DataWorks resources

The server implements the Model Context Protocol specification to standardize cloud resource interactions for AI agents.

Prerequisites

  • Node.js (v16 or higher)
  • pnpm (recommended), npm, or yarn
  • DataWorks Open API with access key and secret key

Installation

Option 1: Install from npm (recommend for clients like Cursor/Cline)

bash
# Install globally
npm install -g alibabacloud-dataworks-mcp-server

# Or install locally in your project
npm install alibabacloud-dataworks-mcp-server

Option 2: Build from Source (for developers)

  1. Clone this repository:
bash
git clone https://github.com/aliyun/alibabacloud-dataworks-mcp-server
cd alibabacloud-dataworks-mcp-server
  1. Install dependencies (pnpm is recommended, npm is supported):
bash
pnpm install
  1. Build the project:
bash
pnpm run build
  1. Development the project (by @modelcontextprotocol/inspector):
bash
pnpm run dev

open http://localhost:5173

Configuration

MCP Server Configuration

If you installed via npm (Option 1):

json
{
  "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",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_UTILS",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

If you built from source (Option 2):

json
{
  "mcpServers": {
    "alibabacloud-dataworks-mcp-server": {
      "command": "node",
      "args": ["/path/to/alibabacloud-dataworks-mcp-server/build/index.js"],
      "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",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_SERVER_IDE_DEFAULT",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Environment Setup

init variables in your environment:

env
# DataWorks Configuration
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
TOOL_CATEGORIES=optional_your_tool_categories_here_ex_SERVER_IDE_DEFAULT
TOOL_NAMES=optional_your_tool_names_here_ex_ListProjects

Configuration Description

  • Use Guide Description Link

Project Structure

alibabacloud-dataworks-mcp-server/
ā”œā”€ā”€ src/
│   ā”œā”€ā”€ index.ts          # Main entry point
ā”œā”€ā”€ package.json
└── tsconfig.json

Available Tools

The MCP server provides the following DataWorks tools:

See this link

Security Considerations

  • Keep your private key secure and never share it
  • Use environment variables for sensitive information
  • Regularly monitor and audit AI agent activities

Troubleshooting

If you encounter issues:

  1. Verify your Aliyun Open API access key and secret key are correct
  2. Check your region id is correct
  3. Ensure you're on the intended network (mainnet, testnet, or devnet)
  4. Verify the build was successful

Dependencies

Key dependencies include:

Contributing

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

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the Apache 2.0 License.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "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",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_UTILS",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      }
    }
  }
}

Use DataWorks MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once DataWorks is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add DataWorks as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the DataWorks MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "dataworks": {
      "command": "npx",
      "args": [
        "-y",
        "alibabacloud-dataworks-mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the DataWorks MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the DataWorks MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use DataWorks to help me with this task?
DataWorks
Sure. I read it.
Here is what I found using DataWorks.

Frequently asked questions

What is the DataWorks MCP server used for?

DataWorks is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use DataWorks MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use DataWorks with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use DataWorks MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With DataWorks connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect DataWorks MCP to TypingMind?

DataWorks runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does DataWorks MCP provide in TypingMind?

DataWorks exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use DataWorks MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If DataWorks requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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