Metroflow Docs

Get productive in under 10 minutes

Self-host the agentic control plane, connect your warehouse and orchestration tools, and open a live semantic graph in the workspace. No row movement. Metadata only.

10 min setup 40+ connectors Apache 2.0

Start here

Pick a guide based on what you need right now. Each path assumes a local Docker install and points to deeper references when you're ready.

Guides

Deeper product and operations guides: workspace workflows, AI agents, deployment, and authentication.

How Metroflow fits your stack

Metroflow sits above your existing data plane, not inside it. Crawlers read metadata from warehouses, transformation projects, and orchestrators, then materialize a living graph your team and agents can reason over.

Nothing copies row data out of Snowflake or Postgres. The crawler ingests schemas, manifests, DAG definitions, and metric metadata, then keeps the graph fresh on a schedule you control.

  • Sources: Snowflake, dbt, Airflow, Supabase, Dagster, and more
  • Crawler: Scheduled metadata ingestion inside your network
  • Graph: Cross-system lineage, ownership, and certified metrics
  • Workspace: UI and agents that understand your stack end to end

What you'll build

By the end of the quickstart path, you'll have a working control plane, not a demo stub.