Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows.
Why this server?
Provides comprehensive access to Apache Airflow's REST API, enabling capabilities such as DAG management, task monitoring, log retrieval, and system health diagnostics.
Why this server?
Allows inspection and operation of Apache Airflow over its REST API, providing tools for managing DAGs, DAG runs, task instances, logs, pools, and import errors.
Why this server?
Allows interaction with Apache Airflow REST API, providing tools to list DAGs, get DAG runs, trigger runs, check task instances, and monitor scheduler health.
Why this server?
Provides tools to interact with Apache Airflow instances to inspect DAGs, monitor DAG runs, retrieve task logs, and perform write operations such as triggering DAGs and clearing task instances.
Why this server?
Provides tools for managing Apache Airflow DAGs, DAG runs, task instances, and logs via the Airflow REST API.
Why this server?
Provides comprehensive tools for managing Amazon MWAA environments and Apache Airflow operations, including DAG management, workflow execution monitoring, task instance tracking, and accessing Airflow connections and variables.
Why this server?
Allows interaction with Apache Airflow through a Model Context Protocol server that wraps Airflow's REST API. Supports DAG management (listing, viewing details, pausing/unpausing), DAG runs (listing, creating), task management (listing tasks and task instances), and system information (health status, version, import errors).
Why this server?
Provides comprehensive access to Apache Airflow's REST API, enabling management of DAGs, DAG runs, tasks, variables, connections, pools, XComs, datasets, and monitoring features. Supports both token-based and basic authentication, with special compatibility for Astronomer Cloud deployments.
Why this server?
Manage Apache Airflow workflows and clusters using natural language commands, including DAG management, task monitoring, pool and variable management, event log analysis, and support for both Airflow 2.x and 3.0+ via dynamic API version selection.