
Alibaba Cloud Ops MCP Server
Alibaba Cloud Ops MCP Server enables seamless integration with Alibaba Cloud APIs, empowering AI agents to automate resource management, monitoring, and DevOps ...
Integrate AlibabaCloud DataWorks with FlowHunt AI agents using the MCP Server for secure, automated, and programmatic control over cloud data workflows.
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.
No specific prompt templates are described in the documentation or code available.
No explicit MCP resource definitions are provided or listed in the available documentation or repository files.
ListProjects
: Tool to list all projects within DataWorks.TOOL_CATEGORIES
and TOOL_NAMES
, suggesting the server exposes multiple DataWorks operation tools, but only ListProjects
is explicitly mentioned.npm install -g alibabacloud-dataworks-mcp-server
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"
}
}
}
}
npm install -g alibabacloud-dataworks-mcp-server
{
"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"
}
}
}
}
npm install -g alibabacloud-dataworks-mcp-server
{
"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"
}
}
}
}
npm install -g alibabacloud-dataworks-mcp-server
{
"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"
}
}
}
}
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.
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.
Section | Availability | Details/Notes |
---|---|---|
Overview | ✅ | Provided in README and repo description |
List of Prompts | ⛔ | No prompt templates found in documentation or code |
List of Resources | ⛔ | No explicit MCP resource definitions found |
List of Tools | ✅ | Tools for DataWorks; ListProjects is explicitly referenced |
Securing API Keys | ✅ | Detailed in configuration examples via env variables |
Sampling Support (less important in evaluation) | ⛔ | Not mentioned |
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.
Has a LICENSE | ✅ (Apache-2.0) |
---|---|
Has at least one tool | ✅ |
Number of Forks | 3 |
Number of Stars | 16 |
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.
It provides a standardized MCP interface for AI agents to interact with Alibaba Cloud DataWorks, enabling management of cloud resources, orchestration of data pipelines, and automation of data workflows via the Open API.
The server exposes tools for managing DataWorks resources, such as 'ListProjects'. Other DataWorks operations may be available based on configuration, but 'ListProjects' is explicitly documented.
Always use environment variables to store sensitive credentials. The server configuration supports setting region and access keys securely via environment variables to avoid hardcoding secrets.
Yes. Add the MCP component to your FlowHunt workflow, configure it with your server’s details, and your AI agent will have access to the DataWorks tools provided by this MCP server.
Typical use cases include cloud resource management, automated data operations (scheduling and monitoring ETL tasks), secure API interactions, and integration with LLM-powered development tools for real-time data insights.
Enable intelligent cloud resource management and automation by integrating the AlibabaCloud DataWorks MCP Server with your FlowHunt AI workflows.
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