Databricks MCP Server

Instructions

Implementation Reference

• src/server/simple_databricks_mcp_server.py:85-94 (handler)

  MCP tool handler for start_cluster that wraps the core API call, handles errors, and returns JSON response.

  @mcp.tool()
  async def start_cluster(cluster_id: str) -> str:
      """Start a terminated Databricks cluster"""
      logger.info(f"Starting cluster: {cluster_id}")
      try:
          result = await clusters.start_cluster(cluster_id)
          return json.dumps(result)
      except Exception as e:
          logger.error(f"Error starting cluster: {str(e)}")
          return json.dumps({"error": str(e)})

• src/api/clusters.py:79-93 (helper)

  Core implementation that performs the actual Databricks API request to start the cluster.

  async def start_cluster(cluster_id: str) -> Dict[str, Any]:
      """
      Start a terminated Databricks cluster.
      
      Args:
          cluster_id: ID of the cluster to start
          
      Returns:
          Empty response on success
          
      Raises:
          DatabricksAPIError: If the API request fails
      """
      logger.info(f"Starting cluster: {cluster_id}")
      return make_api_request("POST", "/api/2.0/clusters/start", data={"cluster_id": cluster_id})