A Model Context Protocol (MCP) server for Apache Dolphinscheduler. This provides access to your Apache Dolphinshcheduler RESTful API V1 instance and
DolphinScheduler MCP server exists for a simple reason — assistants are far more useful when they can act on DolphinScheduler directly instead of describing what you should do. A Model Context Protocol (MCP) server for Apache Dolphinscheduler. This provides access to your Apache Dolphinshcheduler RESTful API V1 instance and the surrounding ecosystem.
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.
The server ships on PyPI as dolphinscheduler-mcp, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
You will need 3 environment variables: DOLPHINSCHEDULER_API_URL, DOLPHINSCHEDULER_API_KEY, DOLPHINSCHEDULER_MCP_HOST. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. It is maintained by ocean-zhc; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against DolphinScheduler's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
{
"mcpServers": {
"dolphinscheduler": {
"command": "uvx",
"args": ["dolphinscheduler-mcp"],
"env": {
"DOLPHINSCHEDULER_API_URL": "your-value",
"DOLPHINSCHEDULER_API_KEY": "your-value",
"DOLPHINSCHEDULER_MCP_HOST": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| DOLPHINSCHEDULER_API_URL | Endpoint or connection string the server talks to. | Yes |
| DOLPHINSCHEDULER_API_KEY | Credential the server authenticates with. | Yes |
| DOLPHINSCHEDULER_MCP_HOST | Endpoint or connection string the server talks to. | Optional |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.