Integration · MODEL CONTEXT PROTOCOL
ocean zhc dolphinscheduler mcp
A Model Context Protocol (MCP) server for Apache Dolphinscheduler. This provides access to your Apache Dolphinshcheduler RESTful API V1 instance and the surrounding ecosystem.
WHAT IT CONNECTS
What ocean zhc dolphinscheduler mcp gives an AI Agent
- 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
- `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)
- 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
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
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.
- 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 APIDOLPHINSCHEDULER_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
COMMUNITY