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JLKmach

ServiceNow MCP Server

by JLKmach

create_epic

Create new epics in ServiceNow to organize large work initiatives, track progress, and manage agile project components with priority, assignment, and detailed descriptions.

Instructions

Create a new epic in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
short_descriptionYesShort description of the epic
descriptionNoDetailed description of the epic
priorityNoPriority of epic (1 is Critical, 2 is High, 3 is Moderate, 4 is Low, 5 is Planning)
stateNoState of story (-6 is Draft,1 is Ready,2 is Work in progress, 3 is Complete, 4 is Cancelled)
assignment_groupNoGroup assigned to the epic
assigned_toNoUser assigned to the epic
work_notesNoWork notes to add to the epic. Used for adding notes and comments to an epic

Implementation Reference

  • The main handler function that implements the create_epic tool logic, including parameter validation, API request preparation, and ServiceNow REST API call to create an epic.
    def create_epic(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Create a new epic in ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for creating the epic.
    
        Returns:
            The created epic.
        """
    
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            CreateEpicParams, 
            required_fields=["short_description"]
        )
        
        if not result["success"]:
            return result
        
        validated_params = result["params"]
        
        # Prepare the request data
        data = {
            "short_description": validated_params.short_description,
        }
           
        # Add optional fields if provided
        if validated_params.description:
            data["description"] = validated_params.description
        if validated_params.priority:
            data["priority"] = validated_params.priority
        if validated_params.assignment_group:
            data["assignment_group"] = validated_params.assignment_group
        if validated_params.assigned_to:
            data["assigned_to"] = validated_params.assigned_to
        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/rm_epic"
        
        try:
            response = requests.post(url, json=data, headers=headers)
            response.raise_for_status()
            
            result = response.json()
            
            return {
                "success": True,
                "message": "Epic created successfully",
                "epic": result["result"],
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error creating epic: {e}")
            return {
                "success": False,
                "message": f"Error creating epic: {str(e)}",
            }
  • Pydantic BaseModel defining the input schema/parameters for the create_epic tool.
    class CreateEpicParams(BaseModel):
        """Parameters for creating an epic."""
    
        short_description: str = Field(..., description="Short description of the epic")
        description: Optional[str] = Field(None, description="Detailed description of the epic")
        priority: Optional[str] = Field(None, description="Priority of epic (1 is Critical, 2 is High, 3 is Moderate, 4 is Low, 5 is Planning)")
        state: Optional[str] = Field(None, description="State of story (-6 is Draft,1 is Ready,2 is Work in progress, 3 is Complete, 4 is Cancelled)")
        assignment_group: Optional[str] = Field(None, description="Group assigned to the epic")
        assigned_to: Optional[str] = Field(None, description="User assigned to the epic")
        work_notes: Optional[str] = Field(None, description="Work notes to add to the epic. Used for adding notes and comments to an epic")
        
    class UpdateEpicParams(BaseModel):
  • Registration of the create_epic tool in the central tool_definitions dictionary, mapping name to handler, schema, return type, description, and serialization method.
    "create_epic": (
        create_epic_tool,
        CreateEpicParams,
        str,
        "Create a new epic in ServiceNow",
        "str",
    ),
  • Import of the create_epic handler aliased as create_epic_tool for use in tool registration.
    from servicenow_mcp.tools.epic_tools import (
        create_epic as create_epic_tool,
        update_epic as update_epic_tool,
        list_epics as list_epics_tool,
    )
  • Helper function used by create_epic to unwrap, validate input parameters against CreateEpicParams 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)}",
            }

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