---

name: service-mcp description: "Data-Juicer FastAPI service, MCP server, operator discovery, and tool-routing workflows." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

service-mcp

Use this sub-skill for Data-Juicer tasks that need the service surface, MCP tools, operator search, or API-style invocation.

Start here

Read these references when the task is not a one-line command:

• references/api-service.md
• references/mcp.md
• references/operator-discovery.md
• references/troubleshooting.md

Owns

• FastAPI service behavior adapted from service.py
• dj-mcp recipe-flow and granular-ops modes
• operator search and route/tool registration
• service transport, request encoding, and plugin-discovery guidance

Excludes

• Local recipe syntax and dataset export basics -> recipes-and-ops
• Ray partition / checkpoint / recovery flows -> ray-and-recovery
• Heavy demo integrations or API-key workflows unless they are only mentioned as non-goals or troubleshooting notes

Common flow

1. Decide whether the user wants a service endpoint or a CLI tool.
2. Read the operator discovery reference if they need search or plugin selection.
3. Use the bundled service script or dj-mcp path that matches the transport.
4. Troubleshoot encoding, transport, or registration issues before changing the recipe itself.

Validation targets

• Can the service or MCP route be invoked without the source checkout?
• Are request parameters encoded the way the route expects?
• Are missing packages, invalid transports, or registration collisions explained clearly?

When to route away

• Any mention of Ray recovery or partitioned jobs
• Any mention of plain dataset processing without service transport