data

Data engineering for Apache Airflow and Astronomer. Author DAGs with best practices, debug pipeline failures, trace data lineage, profile tables, migrate Airflow 2 to 3, and manage local and cloud deployments.

Install

If the official marketplace isn’t added yet, run

Category: Development
GitHub: astronomer/agents

Good for

Author Airflow DAGs with best practices
Debug pipeline failures and trace data lineage
Profile tables and answer business questions with SQL
Migrate Airflow 2 to 3 and manage local and cloud deployments

Getting started

Run /plugin install data@claude-plugins-official
For self-hosted Airflow, set AIRFLOW_API_URL to your instance
Describe the DAG you want to write or debug to Claude

Before you install

The bundled Airflow MCP server runs via uvx from PyPI and works with any Airflow 2.x/3.x REST API; warehouse queries use a background Jupyter kernel.

Summarized by AI from the project docs; check the official docs before relying on it.

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