dolphin-mcp-pilot
Production-ready MCP server for Apache DolphinScheduler. Enables AI agents to operate data workflows end-to-end with 58 tools covering DAG creation, schedule management, instance control, guided troubleshooting, serial backfills, and version rollback.
README
dolphin-mcp-pilot
<div align="center">
</div>
A production-ready MCP server for Apache DolphinScheduler.
dolphin-mcp-pilot exposes 53+ tools for projects, workflows, DAG creation, schedules, instances, resources, logs, monitoring and raw API passthrough — designed for AI agents that need to operate DolphinScheduler beyond basic read-only usage.
🎯 Why this project?
Most public DolphinScheduler MCP servers only cover basic read/list/start/stop scenarios. This project is designed for real operations work:
- ✅ Create SQL / DAG workflows in one line
- ✅ Manage schedules (create / online / offline / delete)
- ✅ Control process instances (pause / resume / rerun / rerun-from-failure)
- ✅ View task logs, force task success / skip failed task
- ✅ Manage resources (view/update content)
- ✅ Roll back workflow versions, clone workflows
- ✅ Use raw API as a safety valve
- ✅ Support multi-tenant per-request auth
🚀 Key features
- 53+ tools covering most practical DS operations
- Two auth modes: API Token (
X-DS-Token) or User/Password (X-DS-User+X-DS-Password) - Multi-tenant HTTP mode: each caller can use its own credentials
- Workflow creation: simple SQL and complex DAG workflows with multiple task types
- Schedule management (cron-based)
- Instance lifecycle control (pause/resume/rerun/rerun-from-failure/delete)
- Resource content management and version rollback / workflow clone
- Raw API passthrough for uncovered edge cases
🚀 Quick Start
# 1. Clone the repository
git clone https://github.com/iflytek/dolphin-mcp-pilot.git
cd dolphin-mcp-pilot
# 2. Configure environment
cp .env.example .env
# Edit .env — at minimum set DS_URL and DS_TOKEN (or DS_USER/DS_PASSWORD)
# 3. Start the service (dev mode)
docker compose --profile dev up -d dolphin-mcp-pilot-dev
✅ Service will be available at http://localhost:8001/mcp/ (note the trailing slash)
📚 Documentation
| Document | Description |
|---|---|
| 📦 Installation | Docker Compose (dev/prod), from source, as package, run modes |
| ⚙️ Configuration | Environment variables, auth options, Compose tunables |
| 🚀 Deployment | Production deployment, Compose reference, verify, troubleshoot |
| 📊 Features | Feature comparison table, tool categories |
| 🔐 Client Config | MCP client setup (CodeBuddy, Claude Desktop, etc.), multi-tenant auth |
| 📖 API Reference | All 53+ tools, parameter conventions, error handling (中文) |
| ❓ FAQ | Common issues and solutions (中文) |
✨ What's new
- Guided troubleshooting:
ds_list_process_instancesattaches anext_actionhint to RUNNING/FAILURE instances, pointing agents tods_list_task_instancesto inspect individual task nodes. - Reliable backfill ordering: serial complement uses the
complementStartDate/complementEndDaterange format so DolphinScheduler generates instances in strict day-by-day order. - Flexible task params:
ds_update_task_paramaccepts bothsnake_caseandcamelCasefield names and reports ignored fields.
🤝 Contributing
Contributions are welcome. See CONTRIBUTING.md for project changes, or follow the example contribution guide to share a tested MCP client configuration.
📄 License
🙏 Acknowledgments
Built with FastMCP and inspired by the Apache DolphinScheduler community.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.