Dataproc MCP Server

Instructions

Args:
    project_id: Google Cloud project ID
    region: Dataproc region
    job_id: Job ID to cancel

Implementation Reference

• src/dataproc_mcp_server/server.py:251-266 (handler)

  MCP tool handler and registration for cancel_job using @mcp.tool() decorator. Delegates to DataprocClient.cancel_job.

  @mcp.tool()
  async def cancel_job(project_id: str, region: str, job_id: str) -> str:
      """Cancel a running job.
  
      Args:
          project_id: Google Cloud project ID
          region: Dataproc region
          job_id: Job ID to cancel
      """
      client = DataprocClient()
      try:
          result = await client.cancel_job(project_id, region, job_id)
          return str(result)
      except Exception as e:
          logger.error("Failed to cancel job", error=str(e))
          return f"Error: {str(e)}"

• src/dataproc_mcp_server/dataproc_client.py:418-440 (helper)

  DataprocClient method that performs the actual job cancellation using Google Cloud Dataproc API client.

  async def cancel_job(
      self, project_id: str, region: str, job_id: str
  ) -> dict[str, Any]:
      """Cancel a running job."""
      try:
          loop = asyncio.get_event_loop()
          client = self._get_job_client(region)
  
          request = types.CancelJobRequest(
              project_id=project_id, region=region, job_id=job_id
          )
  
          job = await loop.run_in_executor(None, client.cancel_job, request)
  
          return {
              "job_id": job.reference.job_id,
              "status": job.status.state.name,
              "message": f"Job {job_id} cancellation requested",
          }
  
      except Exception as e:
          logger.error("Failed to cancel job", error=str(e))
          raise