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Dolphin Mcp Pilot MCP Server

Developer ToolsUse Caution3.2MCP RegistryLocal
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AI agent interface to Apache DolphinScheduler: 58 MCP tools for workflow orchestration & data ops.

About

AI agent interface to Apache DolphinScheduler: 58 MCP tools for workflow orchestration & data ops.

Security Report

3.2
Use Caution3.2High Risk

This MCP server for Apache DolphinScheduler includes significant functionality for workflow automation but has notable security concerns. The codebase lacks proper input validation on user-supplied data structures, includes a hardcoded tenant code that may bypass multi-tenant isolation, and has incomplete error handling. While authentication mechanisms exist (API tokens and user/password), the auth implementation and scope validation are not fully reviewed in the provided code. Permissions align reasonably with the server's stated purpose of managing DolphinScheduler workflows. Supply chain analysis found 6 known vulnerabilities in dependencies (0 critical, 2 high severity).

4 files analyzed · 16 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

File System Write

Writes or modifies files on your machine. Check that this is expected for the tool.

What You'll Need

Set these up before or after installing:

DolphinScheduler API base URL (e.g. http://localhost:12345/dolphinscheduler)Optional

Environment variable: DS_URL

DolphinScheduler API token (leave empty to use DS_USER/DS_PASSWORD instead)Optional

Environment variable: DS_TOKEN

DolphinScheduler username (alternative to DS_TOKEN)Optional

Environment variable: DS_USER

DolphinScheduler password (used with DS_USER)Optional

Environment variable: DS_PASSWORD

Tenant code (default: 'default')Optional

Environment variable: DS_TENANT_CODE

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-iflytek-dolphin-mcp-pilot": {
      "env": {
        "DS_URL": "your-ds-url-here",
        "DS_USER": "your-ds-user-here",
        "DS_TOKEN": "your-ds-token-here",
        "DS_PASSWORD": "your-ds-password-here",
        "DS_TENANT_CODE": "your-ds-tenant-code-here"
      },
      "args": [
        "dolphin-mcp-pilot"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

dolphin-mcp-pilot

License Python CI Ask DeepWiki

English | 简体中文

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
  • MCP 2.0 stateless HTTP with automatic compatibility for MCP 1.x clients
  • 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

Prerequisites

  • A running DolphinScheduler 3.x instance whose API is reachable from Docker
  • Docker with Compose v2 (docker compose version)
  • A DolphinScheduler API token (recommended), or a username and password
# 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 — set DS_URL and DS_TOKEN (or DS_USER/DS_PASSWORD)
# Example DS_URL: http://your-dolphinscheduler-host:12345/dolphinscheduler

# 3. Build and start the service from this checkout
docker compose --profile dev up -d dolphin-mcp-pilot-dev

# 4. Confirm that the container is healthy
docker compose --profile dev ps

The MCP endpoint is now http://localhost:8001/mcp/ (the trailing slash is required). Add it to an HTTP/SSE-capable MCP client:

{
  "mcpServers": {
    "dolphinscheduler": {
      "type": "sse",
      "url": "http://localhost:8001/mcp/",
      "headers": { "X-DS-Token": "your_api_token" }
    }
  }
}

As a safe first check, ask your agent: “List my DolphinScheduler projects and workflows. Do not make any changes.” For client-specific configuration and username/password auth, see Client Config.

💡 Common use cases

ScenarioExample requestMain tools
Investigate a failed run“Find the latest failed workflow, show the failed task and its log, and suggest the next action without changing anything.”ds_list_process_instances, ds_list_task_instances, ds_get_latest_failure_log
Backfill missing data“Backfill 2026-08-01 through 2026-08-07 serially, starting from the validation task and including downstream tasks.”ds_complement_data
Create and schedule a workflow“Create a daily SQL workflow, add its cron schedule, and show me the definition before putting it online.”ds_create_workflow, ds_set_schedule, ds_online_schedule
Give multiple agents controlled accessRun one HTTP MCP service while each caller supplies its own DolphinScheduler credentials.Per-request X-DS-* headers

The tools can also pause, resume, rerun, clone, and roll back workflows; manage resources; and fall back to raw DolphinScheduler APIs for uncovered operations. Start with ds_help(category="quickstart") inside your MCP client to discover the recommended workflow for each task.

📚 Documentation

DocumentDescription
📦 InstallationDocker Compose (dev/prod), from source, as package, run modes
⚙️ ConfigurationEnvironment variables, auth options, Compose tunables
🚀 DeploymentProduction deployment, Compose reference, verify, troubleshoot
📊 FeaturesFeature comparison table, tool categories
🔐 Client ConfigMCP client setup (CodeBuddy, Claude Desktop, etc.), multi-tenant auth
📖 API ReferenceAll 53+ tools, parameter conventions, error handling (中文)
❓ FAQCommon issues and solutions (中文)

✨ What's new

  • MCP 2.0: supports the stateless 2026-07-28 protocol while keeping legacy handshake clients and stdio configurations working.
  • Guided troubleshooting: ds_list_process_instances attaches a next_action hint to RUNNING/FAILURE instances, pointing agents to ds_list_task_instances to inspect individual task nodes.
  • Reliable backfill ordering: serial complement uses the complementStartDate/complementEndDate range format so DolphinScheduler generates instances in strict day-by-day order.
  • Flexible task params: ds_update_task_param accepts both snake_case and camelCase field 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.

Used dolphin-mcp-pilot for something real? Write it up in cases/ — a gallery of community usage stories (agent-driven DolphinScheduler ops), each linked to a public post.

📄 License

Apache-2.0

🙏 Acknowledgments

Built with the official MCP Python SDK and inspired by the Apache DolphinScheduler community.

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