Alibaba Cloud DataWorks MCP Server is a server based on the Model Context Protocol (MCP) that provides tools for AI, enabling it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Alibaba Cloud Open API, allowing AI agents to seamlessly perform cloud resource operations. If your goal is to embed DataWorks capabilities into your own AI workflow or IDE, follow the installation guide below.
Purpose This MCP server is mainly used for: interacting with the DataWorks Open API; managing DataWorks resources. It implements the Model Context Protocol specification, standardizing the way AI agents interact with cloud resources. For users who want to directly obtain the DataWorks intelligent experience without manual MCP configuration, Alibaba Cloud provides a built-in DataWorks Agent—an intelligent assistant for data development and operations that connects to your DataWorks workspace out of the box, allowing you to explore metadata, develop nodes, troubleshoot tasks, and manage resources using natural language. The entry point is:https://dataworks.data.alibabacloud.com/product/agent?source=github
Main capabilities The server provides DataWorks-related tools and implements the MCP specification to unify cloud resource interaction. The materials do not list specific tool names and function details, so they are not provided for now.
Environment requirements
- Node.js (v16 or later)
- pnpm (recommended), npm, or yarn
- DataWorks Open API with an access key and secret key
Usage Two installation methods are provided: Option 1: Install from npm (recommended for clients such as Cursor/Cline) Option 2: Build from source (for developers) Steps to build from source: clone the repository, install dependencies (pnpm recommended, npm also supported), build the project, develop the project using @modelcontextprotocol/inspector, and visit http://localhost:5173。
MCP server configuration If installed via npm (Option 1) or built from source (Option 2), configure it in the corresponding way.
Environment setup Initialize variables in the environment, and complete the setup by referring to the configuration instructions and usage guide links.
Project structure The materials provide a project structure section, but do not list specific directory contents, so they are not provided for now.
Applicable scenarios
- Users who want to embed DataWorks capabilities into their own AI workflow or IDE;
- Scenarios where AI agents need to interact with the DataWorks Open API and manage DataWorks resources through a standardized interface;
- Users who prefer an out-of-the-box experience can use the DataWorks Agent without local MCP configuration.
Limitations and security
- A correct Alibaba Cloud Open API access key and secret key, as well as the correct region id, are required;
- You need to ensure you are on the target network (mainnet, testnet, or devnet);
- You need to verify that the build succeeds. Security notes: keep private keys safe and never share them; use environment variables for sensitive information; regularly monitor and audit AI agent activity.
Troubleshooting If you encounter issues: verify whether the Alibaba Cloud Open API access key and secret key are correct; check whether the region id is correct; ensure you are on the expected network (mainnet, testnet, or devnet); verify whether the build succeeds. Key dependencies include @alicloud/dataworks-public20240518 and @alicloud/openapi-client.
Contributing and license Contributions are welcome; you can submit a Pull Request: Fork the repository, create a feature branch (git checkout -b feature/amazing-feature), commit your changes (git commit -m 'Add some amazing feature'), push the branch (git push origin feature/amazing-feature), and open a Pull Request. The project uses the Apache 2.0 license.
