Dataproc MCP Server

Instructions

Args:
    project_id: Google Cloud project ID
    region: Dataproc region
    batch_id: Batch job ID to delete

Implementation Reference

• src/dataproc_mcp_server/server.py:355-370 (handler)

  MCP tool handler and registration for 'delete_batch_job'. Decorated with @mcp.tool(), delegates to DataprocBatchClient.delete_batch_job.

  @mcp.tool()
  async def delete_batch_job(project_id: str, region: str, batch_id: str) -> str:
      """Delete a batch job.
  
      Args:
          project_id: Google Cloud project ID
          region: Dataproc region
          batch_id: Batch job ID to delete
      """
      batch_client = DataprocBatchClient()
      try:
          result = await batch_client.delete_batch_job(project_id, region, batch_id)
          return str(result)
      except Exception as e:
          logger.error("Failed to delete batch job", error=str(e))
          return f"Error: {str(e)}"

• src/dataproc_mcp_server/batch_client.py:394-417 (helper)

  Core implementation of delete_batch_job in DataprocBatchClient. Calls Google Cloud Dataproc API to delete the batch job.

  async def delete_batch_job(
      self, project_id: str, region: str, batch_id: str
  ) -> dict[str, Any]:
      """Delete a batch job."""
      try:
          loop = asyncio.get_event_loop()
          client = self._get_batch_client(region)
  
          request = types.DeleteBatchRequest(
              name=f"projects/{project_id}/locations/{region}/batches/{batch_id}"
          )
  
          await loop.run_in_executor(None, client.delete_batch, request)
  
          return {
              "batch_id": batch_id,
              "status": "DELETED",
              "message": f"Batch job {batch_id} deletion initiated",
          }
  
      except Exception as e:
          logger.error("Failed to delete batch job", error=str(e))
          raise