dolphinscheduler MCP Server

Use This MCP server To

Automate workflow scheduling and monitoring via AI agents Query and manage DolphinScheduler tasks programmatically Integrate DolphinScheduler with AI-driven orchestration tools Enable AI models to trigger and control data pipelines Fetch real-time workflow status and logs for analysis Configure and update workflows through AI commands

README

DolphinScheduler MCP Server

A Model Context Protocol (MCP) server for Apache DolphinScheduler, allowing AI agents to interact with DolphinScheduler through a standardized protocol.

Overview

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.

Features

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

Installation

pip install dolphinscheduler-mcp

Configuration

Environment Variables

DOLPHINSCHEDULER_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)

Usage

Command Line

Start the server using the command-line interface:

ds-mcp --host 0.0.0.0 --port 8089

Python API

from dolphinscheduler_mcp.server import run_server

# Start the server
run_server(host="0.0.0.0", port=8089)

Available Tools

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

Example Client Usage

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"}
)

License

Apache License 2.0

dolphinscheduler-mcp FAQ

How do I install the DolphinScheduler MCP server?

Install it easily using pip with the command `pip install dolphinscheduler-mcp`.

How do I configure the DolphinScheduler MCP server?

Configure it using environment variables like `DOLPHINSCHEDULER_API_URL` and `DOLPHINSCHEDULER_API_KEY` or command-line arguments.

What authentication methods does the server support?

It supports API key authentication to securely connect to your DolphinScheduler instance.

Can I use this MCP server with different AI models?

Yes, it is provider-agnostic and works with models like OpenAI GPT-4, Anthropic Claude, and Google Gemini.

Does the server cover all DolphinScheduler API features?

Yes, it provides full API coverage of DolphinScheduler's RESTful endpoints.

Is there documentation available for the tools exposed?

Yes, comprehensive tool documentation is included to help you understand and use the interfaces effectively.

How does this server help in AI-driven workflow management?

It enables AI agents to interact with DolphinScheduler workflows programmatically, automating scheduling, monitoring, and control tasks.

Can I run the server locally?

Yes, the server can be run locally and configured to connect to your DolphinScheduler instance via the API URL.