get_task_instance
Retrieve detailed information about a specific task instance in an Amazon MWAA environment by providing the environment name, DAG ID, run ID, and task ID for workflow monitoring and troubleshooting.
Instructions
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
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| environment_name | Yes | ||
| dag_id | Yes | ||
| dag_run_id | Yes | ||
| task_id | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- awslabs/mwaa_mcp_server/tools.py:343-351 (handler)The core handler for 'get_task_instance' that invokes the MWAA REST API.
async def get_task_instance( self, environment_name: str, dag_id: str, dag_run_id: str, task_id: str ) -> Dict[str, Any]: """Get task instance details via Airflow API.""" return self._invoke_airflow_api( environment_name, "GET", f"/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}", ) - awslabs/mwaa_mcp_server/server.py:388-406 (registration)The MCP tool registration and entry point for 'get_task_instance'.
@mcp.tool(name="get_task_instance") async def get_task_instance( environment_name: str, dag_id: str, dag_run_id: str, task_id: str, ) -> Dict[str, Any]: """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 """ return await tools.get_task_instance(environment_name, dag_id, dag_run_id, task_id)