update_workflow
Modify workflow settings in ServiceNow by updating attributes like name, description, active status, and associated table using the Workflow ID.
Instructions
Update an existing workflow in ServiceNow
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Implementation Reference
- The main execution function (handler) for the update_workflow tool. It validates input using UpdateWorkflowParams, prepares the update payload, and performs a PATCH request to the ServiceNow wf_workflow table endpoint.def update_workflow( auth_manager: AuthManager, server_config: ServerConfig, params: Dict[str, Any], ) -> Dict[str, Any]: """ Update an existing workflow in ServiceNow. Args: auth_manager: Authentication manager server_config: Server configuration params: Parameters for updating a workflow Returns: Dict[str, Any]: Updated workflow details """ # Unwrap parameters if needed params = _unwrap_params(params, UpdateWorkflowParams) # Get the correct auth_manager and server_config try: auth_manager, server_config = _get_auth_and_config(auth_manager, server_config) except ValueError as e: logger.error(f"Error getting auth and config: {e}") return {"error": str(e)} workflow_id = params.get("workflow_id") if not workflow_id: return {"error": "Workflow ID is required"} # Prepare data for the API request data = {} if params.get("name"): data["name"] = params["name"] if params.get("description") is not None: data["description"] = params["description"] if params.get("table"): data["table"] = params["table"] if params.get("active") is not None: data["active"] = str(params["active"]).lower() if params.get("attributes"): # Add any additional attributes data.update(params["attributes"]) if not data: return {"error": "No update parameters provided"} # Make the API request try: headers = auth_manager.get_headers() url = f"{server_config.instance_url}/api/now/table/wf_workflow/{workflow_id}" response = requests.patch(url, headers=headers, json=data) response.raise_for_status() result = response.json() return { "workflow": result.get("result", {}), "message": "Workflow updated successfully", } except requests.RequestException as e: logger.error(f"Error updating workflow: {e}") return {"error": str(e)} except Exception as e: logger.error(f"Unexpected error updating workflow: {e}") return {"error": str(e)}
- Pydantic BaseModel defining the input schema for the update_workflow tool, with workflow_id required and other fields optional.class UpdateWorkflowParams(BaseModel): """Parameters for updating a workflow.""" workflow_id: str = Field(..., description="Workflow ID or sys_id") name: Optional[str] = Field(None, description="Name of the workflow") description: Optional[str] = Field(None, description="Description of the workflow") table: Optional[str] = Field(None, description="Table the workflow applies to") active: Optional[bool] = Field(None, description="Whether the workflow is active") attributes: Optional[Dict[str, Any]] = Field(None, description="Additional attributes for the workflow")
- src/servicenow_mcp/utils/tool_utils.py:582-588 (registration)Tool registration entry in get_tool_definitions() dict, specifying the aliased handler function, input schema model, input/return types, description, and serialization method for MCP server integration."update_workflow": ( update_workflow_tool, UpdateWorkflowParams, str, # Expects JSON string "Update an existing workflow in ServiceNow", "json_dict", # Tool returns Pydantic model ),
- Helper function to unwrap and normalize input parameters, converting Pydantic models to dicts if necessary; used at line 536 in the handler.def _unwrap_params(params: Any, param_class: Type[T]) -> Dict[str, Any]: """ Unwrap parameters if they're wrapped in a Pydantic model. This helps handle cases where the parameters are passed as a model instead of a dict. """ if isinstance(params, dict): return params if isinstance(params, param_class): return params.dict(exclude_none=True) return params
- Helper function to normalize auth_manager and server_config arguments, handling potential order swap; used in the handler.def _get_auth_and_config( auth_manager_or_config: Union[AuthManager, ServerConfig], server_config_or_auth: Union[ServerConfig, AuthManager], ) -> tuple[AuthManager, ServerConfig]: """ Get the correct auth_manager and server_config objects. This function handles the case where the parameters might be swapped. Args: auth_manager_or_config: Either an AuthManager or a ServerConfig. server_config_or_auth: Either a ServerConfig or an AuthManager. Returns: tuple[AuthManager, ServerConfig]: The correct auth_manager and server_config. Raises: ValueError: If the parameters are not of the expected types. """ # Check if the parameters are in the correct order if isinstance(auth_manager_or_config, AuthManager) and isinstance(server_config_or_auth, ServerConfig): return auth_manager_or_config, server_config_or_auth # Check if the parameters are swapped if isinstance(auth_manager_or_config, ServerConfig) and isinstance(server_config_or_auth, AuthManager): return server_config_or_auth, auth_manager_or_config # If we get here, at least one of the parameters is not of the expected type if hasattr(auth_manager_or_config, "get_headers"): auth_manager = auth_manager_or_config elif hasattr(server_config_or_auth, "get_headers"): auth_manager = server_config_or_auth else: raise ValueError("Cannot find get_headers method in either auth_manager or server_config") if hasattr(auth_manager_or_config, "instance_url"): server_config = auth_manager_or_config elif hasattr(server_config_or_auth, "instance_url"): server_config = server_config_or_auth else: raise ValueError("Cannot find instance_url attribute in either auth_manager or server_config") return auth_manager, server_config