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DolphinScheduler MCP Server

DolphinScheduler MCP Server

Local
github.com/ocean-zhcCloud & Infra29Updated 76w ago
Repository

About DolphinScheduler MCP Server

DolphinScheduler MCP Server is an MCP server that exposes the Apache DolphinScheduler REST API as tools for AI agents. It is aimed at teams that manage scheduled workflows and want AI-driven control over them.

Key features

  1. 01Covers project, process, task and scheduling management
  2. 02Configurable through environment variables or command-line arguments
  3. 03Can be started from the command line or the Python API
  4. 04Authenticates with an API token

Use cases

  1. 01Letting an AI agent query and manage process instances
  2. 02Checking scheduling status and alert group setup through an assistant

MCP support

This project is an MCP server that exposes DolphinScheduler REST API operations as tools for MCP clients.

#dolphinscheduler#mcp#api-server

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project 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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.