ServiceNow MCP Server

Instructions

Implementation Reference

• src/servicenow_mcp/tools/change_tools.py:584-667 (handler)

  Core handler function that executes the add_change_task tool: validates params, prepares data, makes POST request to ServiceNow change_task table, returns result.
  def add_change_task( auth_manager: AuthManager, server_config: ServerConfig, params: Dict[str, Any], ) -> Dict[str, Any]: """ Add a task to a change request in ServiceNow. Args: auth_manager: The authentication manager. server_config: The server configuration. params: The parameters for adding a change task. Returns: The created change task. """ # Unwrap and validate parameters result = _unwrap_and_validate_params( params, AddChangeTaskParams, required_fields=["change_id", "short_description"] ) if not result["success"]: return result validated_params = result["params"] # Prepare the request data data = { "change_request": validated_params.change_id, "short_description": validated_params.short_description, } # Add optional fields if provided if validated_params.description: data["description"] = validated_params.description if validated_params.assigned_to: data["assigned_to"] = validated_params.assigned_to if validated_params.planned_start_date: data["planned_start_date"] = validated_params.planned_start_date if validated_params.planned_end_date: data["planned_end_date"] = validated_params.planned_end_date # Get the instance URL instance_url = _get_instance_url(auth_manager, server_config) if not instance_url: return { "success": False, "message": "Cannot find instance_url in either server_config or auth_manager", } # Get the headers headers = _get_headers(auth_manager, server_config) if not headers: return { "success": False, "message": "Cannot find get_headers method in either auth_manager or server_config", } # Add Content-Type header headers["Content-Type"] = "application/json" # Make the API request url = f"{instance_url}/api/now/table/change_task" try: response = requests.post(url, json=data, headers=headers) response.raise_for_status() result = response.json() return { "success": True, "message": "Change task added successfully", "change_task": result["result"], } except requests.exceptions.RequestException as e: logger.error(f"Error adding change task: {e}") return { "success": False, "message": f"Error adding change task: {str(e)}", }
• src/servicenow_mcp/tools/change_tools.py:73-82 (schema)

  Pydantic model defining the input schema and validation for add_change_task parameters.
  class AddChangeTaskParams(BaseModel): """Parameters for adding a task to a change request.""" change_id: str = Field(..., description="Change request ID or sys_id") short_description: str = Field(..., description="Short description of the task") description: Optional[str] = Field(None, description="Detailed description of the task") assigned_to: Optional[str] = Field(None, description="User assigned to the task") planned_start_date: Optional[str] = Field(None, description="Planned start date (YYYY-MM-DD HH:MM:SS)") planned_end_date: Optional[str] = Field(None, description="Planned end date (YYYY-MM-DD HH:MM:SS)")
• src/servicenow_mcp/utils/tool_utils.py:461-467 (registration)

  Registers the add_change_task tool in the central get_tool_definitions() dictionary, mapping name to handler, schema, return type, description, and serialization method for MCP server.
  "add_change_task": ( add_change_task_tool, AddChangeTaskParams, str, # Expects JSON string "Add a task to a change request", "json_dict", # Tool returns Pydantic model ),
• src/servicenow_mcp/tools/__init__.py:23-32 (registration)

  Re-exports add_change_task from change_tools.py to make it available at the tools package level.
  from servicenow_mcp.tools.change_tools import ( add_change_task, approve_change, create_change_request, get_change_request_details, list_change_requests, reject_change, submit_change_for_approval, update_change_request, )
• src/servicenow_mcp/tools/change_tools.py:107-159 (helper)

  Shared helper function used by add_change_task (and other tools) to unwrap, validate input parameters against the Pydantic schema, handling various input formats.
  def _unwrap_and_validate_params(params: Any, model_class: Type[T], required_fields: List[str] = None) -> Dict[str, Any]: """ Helper function to unwrap and validate parameters. Args: params: The parameters to unwrap and validate. model_class: The Pydantic model class to validate against. required_fields: List of required field names. Returns: A tuple of (success, result) where result is either the validated parameters or an error message. """ # Handle case where params might be wrapped in another dictionary if isinstance(params, dict) and len(params) == 1 and "params" in params and isinstance(params["params"], dict): logger.warning("Detected params wrapped in a 'params' key. Unwrapping...") params = params["params"] # Handle case where params might be a Pydantic model object if not isinstance(params, dict): try: # Try to convert to dict if it's a Pydantic model logger.warning("Params is not a dictionary. Attempting to convert...") params = params.dict() if hasattr(params, "dict") else dict(params) except Exception as e: logger.error(f"Failed to convert params to dictionary: {e}") return { "success": False, "message": f"Invalid parameters format. Expected a dictionary, got {type(params).__name__}", } # Validate required parameters are present if required_fields: for field in required_fields: if field not in params: return { "success": False, "message": f"Missing required parameter '{field}'", } try: # Validate parameters against the model validated_params = model_class(**params) return { "success": True, "params": validated_params, } except Exception as e: logger.error(f"Error validating parameters: {e}") return { "success": False, "message": f"Error validating parameters: {str(e)}", }