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Metaflow MCP Server

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Give your coding agent superpowers over your Metaflow workflows. Instead of writing throwaway scripts to check run status or dig through logs, just ask -- your agent will figure out the rest.

Works with any Metaflow backend: local, S3, Azure, GCS, or Netflix internal.

demo

Tools

Tool Description
get_config What backend am I connected to? (also returns your default namespace)
list_flows What flows exist in a namespace?
search_runs Find recent runs of any flow
get_run Step-by-step breakdown of a run
get_task_logs Pull stdout/stderr from a task
list_artifacts What did this step produce?
get_artifact Grab an artifact's value
get_latest_failure What broke and why?
search_artifacts Which runs produced a named artifact?

Quickstart

pip install metaflow-mcp-server
claude mcp add --scope user metaflow -- metaflow-mcp-server

That's it. Restart Claude Code and start asking questions about your flows.

To upgrade:

pip install --upgrade metaflow-mcp-server

Then restart Claude Code (or reconnect via /mcp) to pick up the new version.

If Metaflow lives in a specific venv, point to it:

claude mcp add --scope user metaflow -- /path/to/venv/bin/metaflow-mcp-server

For other MCP clients, the server speaks stdio: metaflow-mcp-server

How it works

Wraps the Metaflow client API. Whatever backend your Metaflow is pointed at, the server uses too -- no separate config needed. Sets namespace(None) at startup so production runs (Argo, Step Functions, Maestro) are visible alongside your dev runs.

Starts once per session, communicates over stdin/stdout. No daemon, no port.

License

Apache-2.0

About

MCP server to inspect Metaflow runs, logs, and artifacts from your coding agent.

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