Provides tools for interacting with Apache DolphinScheduler's REST API, enabling AI-driven workflow management including project management, process definition and instance management, task management, resource management, data source management, and system monitoring.
Offers a Python API for starting and configuring the MCP server, as well as client libraries for invoking DolphinScheduler tools programmatically through Python.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@DolphinScheduler MCP Server list all scheduled workflows for the analytics project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server for Apache DolphinScheduler, allowing AI agents to interact with DolphinScheduler through a standardized protocol.
DolphinScheduler MCP provides a FastMCP-based server that exposes DolphinScheduler's REST API as a collection of tools that can be used by AI agents. The server acts as a bridge between AI models and DolphinScheduler, enabling AI-driven workflow management.
Related MCP server: DataWorks MCP Server
Full API coverage of DolphinScheduler functionality
Standardized tool interfaces following the Model Context Protocol
Easy configuration through environment variables or command-line arguments
Comprehensive tool documentation
pip install dolphinscheduler-mcpDOLPHINSCHEDULER_API_URL: URL for the DolphinScheduler API (default: http://localhost:12345/dolphinscheduler)
DOLPHINSCHEDULER_API_KEY: API token for authentication with the DolphinScheduler API
DOLPHINSCHEDULER_MCP_HOST: Host to bind the MCP server (default: 0.0.0.0)
DOLPHINSCHEDULER_MCP_PORT: Port to bind the MCP server (default: 8089)
DOLPHINSCHEDULER_MCP_LOG_LEVEL: Logging level (default: INFO)
Start the server using the command-line interface:
ds-mcp --host 0.0.0.0 --port 8089from dolphinscheduler_mcp.server import run_server
# Start the server
run_server(host="0.0.0.0", port=8089)The DolphinScheduler MCP Server provides tools for:
Project Management
Process Definition Management
Process Instance Management
Task Definition Management
Scheduling Management
Resource Management
Data Source Management
Alert Group Management
Alert Plugin Management
Worker Group Management
Tenant Management
User Management
System Status Monitoring
from mcp_client import MCPClient
# Connect to the MCP server
client = MCPClient("http://localhost:8089/mcp")
# Get a list of projects
response = await client.invoke_tool("get-project-list")
# Create a new project
response = await client.invoke_tool(
"create-project",
{"name": "My AI Project", "description": "Project created by AI"}
)Apache License 2.0
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If you are the server author, to access and configure the admin panel.
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