MWAA MCP Server

List all MWAA environments in the current AWS account and region.

Args: max_results: Maximum number of environments to return (1-25)

Returns: Dictionary containing list of environment names and metadata

Get detailed information about a specific MWAA environment.

Args: name: The name of the MWAA environment

Returns: Dictionary containing environment details including configuration, status, endpoints, and other metadata

Create a new MWAA environment.

Args: name: Environment name dag_s3_path: S3 path to DAGs folder (e.g., s3://bucket/dags) execution_role_arn: IAM role ARN for the environment network_configuration: VPC configuration with SubnetIds and SecurityGroupIds source_bucket_arn: ARN of the S3 bucket containing DAGs airflow_version: Apache Airflow version (e.g., "2.7.2") environment_class: Environment size (mw1.small, mw1.medium, mw1.large, mw1.xlarge, mw1.2xlarge) max_workers: Maximum number of workers (1-25) min_workers: Minimum number of workers (1-25) schedulers: Number of schedulers (2-5) webserver_access_mode: PUBLIC_ONLY or PRIVATE_ONLY weekly_maintenance_window_start: Maintenance window start (e.g., "SUN:03:00") tags: Resource tags airflow_configuration_options: Airflow configuration overrides logging_configuration: Logging settings for different components requirements_s3_path: S3 path to requirements.txt plugins_s3_path: S3 path to plugins.zip startup_script_s3_path: S3 path to startup script

Returns: Dictionary containing the ARN of the created environment

Update an existing MWAA environment configuration.

Only provide the parameters you want to change.

Args: name: Environment name dag_s3_path: S3 path to DAGs folder execution_role_arn: IAM role ARN network_configuration: VPC configuration source_bucket_arn: S3 bucket ARN airflow_version: Apache Airflow version environment_class: Environment size max_workers: Maximum workers min_workers: Minimum workers schedulers: Number of schedulers webserver_access_mode: Access mode weekly_maintenance_window_start: Maintenance window airflow_configuration_options: Configuration overrides logging_configuration: Logging settings requirements_s3_path: Path to requirements.txt plugins_s3_path: Path to plugins.zip startup_script_s3_path: Path to startup script

Returns: Dictionary containing the environment ARN

Delete an MWAA environment.

Args: name: The name of the environment to delete

Returns: Dictionary with deletion confirmation

Create a CLI token for executing Airflow CLI commands.

Args: name: The name of the MWAA environment

Returns: Dictionary containing the CLI token and webserver hostname

Create a web login token for accessing the Airflow UI.

Args: name: The name of the MWAA environment

Returns: Dictionary containing the web token, webserver hostname, and IAM identity

List all DAGs in an MWAA environment.

Args: environment_name: Name of the MWAA environment limit: Number of items to return (max 100) offset: Number of items to skip tags: Filter by DAG tags dag_id_pattern: Filter by DAG ID pattern (supports % wildcards) only_active: Only return active DAGs

Returns: Dictionary containing list of DAGs with their details

Get details about a specific DAG.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID

Returns: Dictionary containing DAG details including schedule, tags, and state

Get the source code of a DAG.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID

Returns: Dictionary containing the DAG source code

Trigger a new DAG run.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID to trigger dag_run_id: Custom run ID (optional, will be auto-generated if not provided) conf: Configuration JSON for the DAG run note: Optional note for the DAG run

Returns: Dictionary containing the created DAG run details

Get details about a specific DAG run.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID dag_run_id: The DAG run ID

Returns: Dictionary containing DAG run details including state and timing

List DAG runs for a specific DAG.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID limit: Number of items to return state: Filter by state (queued, running, success, failed) execution_date_gte: Filter by execution date >= (ISO format) execution_date_lte: Filter by execution date <= (ISO format)

Returns: Dictionary containing list of DAG runs

Get details about a specific task instance.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID dag_run_id: The DAG run ID task_id: The task ID

Returns: Dictionary containing task instance details

Get logs for a specific task instance.

Args: environment_name: Name of the MWAA environment dag_id: The DAG ID dag_run_id: The DAG run ID task_id: The task ID task_try_number: Specific try number (optional)

Returns: Dictionary containing task logs

List task instances across DAGs with flexible time-based filtering.

This is the key tool for finding what tasks were running during a specific time window. Supports wildcards: omit dag_id or dag_run_id to query across all DAGs/runs.

Args: environment_name: Name of the MWAA environment dag_id: Filter by DAG ID (optional - omit for all DAGs) dag_run_id: Filter by DAG run ID (optional - omit for all runs) start_date_gte: Tasks that started at or after this time (ISO format) start_date_lte: Tasks that started at or before this time (ISO format) end_date_gte: Tasks that ended at or after this time (ISO format) end_date_lte: Tasks that ended at or before this time (ISO format) execution_date_gte: Filter by execution/logical date >= (ISO format) execution_date_lte: Filter by execution/logical date <= (ISO format) state: Filter by state (queued, running, success, failed, etc.) pool: Filter by pool name queue: Filter by queue name duration_gte: Filter by minimum duration in seconds duration_lte: Filter by maximum duration in seconds limit: Number of items to return (default 100) offset: Number of items to skip for pagination

Returns: Dictionary containing list of task instances with details

Example - Find tasks running between 2:30-2:40 AM: list_task_instances( environment_name="my-env", start_date_lte="2024-01-15T02:40:00Z", # Started before 2:40 end_date_gte="2024-01-15T02:30:00Z", # Ended after 2:30 (or still running) )

List all Airflow connections in the environment.

Args: environment_name: Name of the MWAA environment limit: Number of items to return offset: Number of items to skip

Returns: Dictionary containing list of connections

List all Airflow variables in the environment.

Args: environment_name: Name of the MWAA environment limit: Number of items to return offset: Number of items to skip

Returns: Dictionary containing list of variables

Get DAG import errors in the environment.

Args: environment_name: Name of the MWAA environment limit: Number of items to return offset: Number of items to skip

Returns: Dictionary containing list of import errors

Get MWAA and Apache Airflow best practices guidance.

Returns comprehensive guidance on:

• DAG design patterns

• Performance optimization

• Resource management

• Error handling

• Security best practices

• MWAA-specific considerations

Get detailed guidance on designing efficient Airflow DAGs.

Returns expert guidance on:

• Task dependencies and parallelism

• Dynamic DAG generation

• Sensor patterns

• XCom usage

• Testing strategies

• Common pitfalls to avoid