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JLKmach

ServiceNow MCP Server

by JLKmach

list_epics

Retrieve and filter epics from ServiceNow to manage agile project initiatives, with options for priority, assignment group, and timeframe.

Instructions

List epics from ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return
offsetNoOffset to start from
priorityNoFilter by priority
assignment_groupNoFilter by assignment group
timeframeNoFilter by timeframe (upcoming, in-progress, completed)
queryNoAdditional query string

Implementation Reference

  • The core handler function that executes the list_epics tool. It validates parameters using ListEpicsParams, builds a ServiceNow query, and fetches epics via the REST API.
    def list_epics( auth_manager: AuthManager, server_config: ServerConfig, params: Dict[str, Any], ) -> Dict[str, Any]: """ List epics from ServiceNow. Args: auth_manager: The authentication manager. server_config: The server configuration. params: The parameters for listing epics. Returns: A list of epics. """ # Unwrap and validate parameters result = _unwrap_and_validate_params( params, ListEpicsParams ) if not result["success"]: return result validated_params = result["params"] # Build the query query_parts = [] if validated_params.priority: query_parts.append(f"priority={validated_params.priority}") if validated_params.assignment_group: query_parts.append(f"assignment_group={validated_params.assignment_group}") # Handle timeframe filtering if validated_params.timeframe: now = datetime.now().strftime("%Y-%m-%d %H:%M:%S") if validated_params.timeframe == "upcoming": query_parts.append(f"start_date>{now}") elif validated_params.timeframe == "in-progress": query_parts.append(f"start_date<{now}^end_date>{now}") elif validated_params.timeframe == "completed": query_parts.append(f"end_date<{now}") # Add any additional query string if validated_params.query: query_parts.append(validated_params.query) # Combine query parts query = "^".join(query_parts) if query_parts else "" # 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", } # Make the API request url = f"{instance_url}/api/now/table/rm_epic" params = { "sysparm_limit": validated_params.limit, "sysparm_offset": validated_params.offset, "sysparm_query": query, "sysparm_display_value": "true", } try: response = requests.get(url, headers=headers, params=params) response.raise_for_status() result = response.json() # Handle the case where result["result"] is a list epics = result.get("result", []) count = len(epics) return { "success": True, "epics": epics, "count": count, "total": count, # Use count as total if total is not provided } except requests.exceptions.RequestException as e: logger.error(f"Error listing epics: {e}") return { "success": False, "message": f"Error listing epics: {str(e)}", }
  • Pydantic BaseModel defining the input schema/parameters for the list_epics tool, including filters like limit, priority, timeframe, etc.
    class ListEpicsParams(BaseModel): """Parameters for listing epics.""" limit: Optional[int] = Field(10, description="Maximum number of records to return") offset: Optional[int] = Field(0, description="Offset to start from") priority: Optional[str] = Field(None, description="Filter by priority") assignment_group: Optional[str] = Field(None, description="Filter by assignment group") timeframe: Optional[str] = Field(None, description="Filter by timeframe (upcoming, in-progress, completed)") query: Optional[str] = Field(None, description="Additional query string")
  • Tool registration in get_tool_definitions() dictionary, associating 'list_epics' name with its handler (list_epics_tool), schema (ListEpicsParams), description, and serialization settings.
    "list_epics": ( list_epics_tool, ListEpicsParams, str, # Expects JSON string "List epics from ServiceNow", "json", # Tool returns list/dict ),
  • Import of list_epics handler in tools/__init__.py, exposing it for use in tool_utils.py imports.
    list_epics,
  • Shared helper function used by list_epics (and other tools) to unwrap, validate 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)}", }

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