ServiceNow MCP Server

Instructions

Implementation Reference

• src/servicenow_mcp/tools/change_tools.py:302-394 (handler)

  The main handler function for the update_change_request tool. It validates input parameters using Pydantic, prepares the update data, constructs the ServiceNow API URL, and performs a PUT request to update the change request.
  def update_change_request( auth_manager: AuthManager, server_config: ServerConfig, params: Dict[str, Any], ) -> Dict[str, Any]: """ Update an existing change request in ServiceNow. Args: auth_manager: The authentication manager. server_config: The server configuration. params: The parameters for updating the change request. Returns: The updated change request. """ # Unwrap and validate parameters result = _unwrap_and_validate_params( params, UpdateChangeRequestParams, required_fields=["change_id"] ) if not result["success"]: return result validated_params = result["params"] # Prepare the request data data = {} # Add fields if provided if validated_params.short_description: data["short_description"] = validated_params.short_description if validated_params.description: data["description"] = validated_params.description if validated_params.state: data["state"] = validated_params.state if validated_params.risk: data["risk"] = validated_params.risk if validated_params.impact: data["impact"] = validated_params.impact if validated_params.category: data["category"] = validated_params.category if validated_params.assignment_group: data["assignment_group"] = validated_params.assignment_group if validated_params.start_date: data["start_date"] = validated_params.start_date if validated_params.end_date: data["end_date"] = validated_params.end_date if validated_params.work_notes: data["work_notes"] = validated_params.work_notes # 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_request/{validated_params.change_id}" try: response = requests.put(url, json=data, headers=headers) response.raise_for_status() result = response.json() return { "success": True, "message": "Change request updated successfully", "change_request": result["result"], } except requests.exceptions.RequestException as e: logger.error(f"Error updating change request: {e}") return { "success": False, "message": f"Error updating change request: {str(e)}", }
• src/servicenow_mcp/tools/change_tools.py:38-52 (schema)

  Pydantic BaseModel defining the input schema for the update_change_request tool, including required change_id and optional fields for updating the change request.
  class UpdateChangeRequestParams(BaseModel): """Parameters for updating a change request.""" change_id: str = Field(..., description="Change request ID or sys_id") short_description: Optional[str] = Field(None, description="Short description of the change request") description: Optional[str] = Field(None, description="Detailed description of the change request") state: Optional[str] = Field(None, description="State of the change request") risk: Optional[str] = Field(None, description="Risk level of the change") impact: Optional[str] = Field(None, description="Impact of the change") category: Optional[str] = Field(None, description="Category of the change") assignment_group: Optional[str] = Field(None, description="Group assigned to the change") start_date: Optional[str] = Field(None, description="Planned start date (YYYY-MM-DD HH:MM:SS)") end_date: Optional[str] = Field(None, description="Planned end date (YYYY-MM-DD HH:MM:SS)") work_notes: Optional[str] = Field(None, description="Work notes to add to the change request")
• src/servicenow_mcp/utils/tool_utils.py:440-446 (registration)

  Registration of the update_change_request tool in the central tool_definitions dictionary used by the MCP server, mapping the tool name to its handler function, input schema, return type, description, and serialization method.
  "update_change_request": ( update_change_request_tool, UpdateChangeRequestParams, str, "Update an existing change request in ServiceNow", "str", ),
• src/servicenow_mcp/tools/change_tools.py:107-159 (helper)

  Shared helper function used by the handler (and other tools) to unwrap, validate required fields, and parse input parameters against the Pydantic schema.
  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)}", }