How does the adapter handle different API versions?

The skill features an auto-detection mechanism that identifies the Airflow version at startup and routes requests through the appropriate adapter.

Does this skill support the latest Airflow 3.x release?

Yes, it includes a dedicated adapter specifically designed for Airflow 3.x utilizing the /api/v2 endpoints.

Where can I find documentation on the API differences?

The skill references an api-differences.md file within the repository that details the specific field and endpoint changes between versions.

Can I use this to trigger DAGs with custom parameters?

Absolutely. The adapter's trigger_dag_run method supports passing configuration dictionaries directly to your Airflow tasks.

Is this tool compatible with Astronomer hosted Airflow?

Yes, as part of the Astronomer agents ecosystem, it is designed to work with standard Apache Airflow and Astronomer-managed environments.

Airflow API Adapter

Name: Airflow API Adapter
Author: astronomer

byastronomer

•

Data Science & ML

Standardizes interactions across Apache Airflow 2.x and 3.x API versions for seamless data pipeline orchestration.

About

The Airflow Adapter skill provides a unified interface for Claude to interact with Apache Airflow environments regardless of their version. By abstracting the differences between Airflow 2.x (/api/v1) and Airflow 3.x (/api/v2), it allows Claude to list DAGs, trigger runs, and manage workflows without worrying about breaking changes in underlying API endpoints. This skill is essential for data engineers managing hybrid environments or performing migrations, as it ensures consistent behavior and reduces errors when automating complex data workflows.

Key Features

Automatic version detection for Airflow 2.x and 3.x environments
Unified interface for cross-version API compatibility
77 GitHub stars
Standardized DAG management including listing and triggering runs
Detailed mapping of endpoint differences between Airflow V2 and V3
Simplified implementation pattern for data engineering agents

Use Cases

Automating complex DAG execution sequences via a consistent AI interface
Managing data pipelines across diverse or legacy Airflow deployments
Facilitating smooth migrations from Airflow 2.x to Airflow 3.x

About

Key Features

Automatic version detection for Airflow 2.x and 3.x environments
Unified interface for cross-version API compatibility
77 GitHub stars
Standardized DAG management including listing and triggering runs
Detailed mapping of endpoint differences between Airflow V2 and V3
Simplified implementation pattern for data engineering agents

Use Cases

Automating complex DAG execution sequences via a consistent AI interface
Managing data pipelines across diverse or legacy Airflow deployments
Facilitating smooth migrations from Airflow 2.x to Airflow 3.x