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JLKmach

ServiceNow MCP Server

by JLKmach

list_changesets

Retrieve and filter ServiceNow changesets to monitor application updates, track developer contributions, and review recent modifications with customizable parameters.

Instructions

List changesets from ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return
offsetNoOffset to start from
stateNoFilter by state
applicationNoFilter by application
developerNoFilter by developer
timeframeNoFilter by timeframe (recent, last_week, last_month)
queryNoAdditional query string

Implementation Reference

  • The handler function that executes the tool logic: validates params, builds ServiceNow API query for sys_update_set table, fetches and returns changesets.
    def list_changesets( auth_manager: AuthManager, server_config: ServerConfig, params: Union[Dict[str, Any], ListChangesetsParams], ) -> Dict[str, Any]: """ List changesets from ServiceNow. Args: auth_manager: The authentication manager. server_config: The server configuration. params: The parameters for listing changesets. Can be a dictionary or a ListChangesetsParams object. Returns: A list of changesets. """ # Unwrap and validate parameters result = _unwrap_and_validate_params(params, ListChangesetsParams) if not result["success"]: return result validated_params = result["params"] # 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", } # Build query parameters query_params = { "sysparm_limit": validated_params.limit, "sysparm_offset": validated_params.offset, } # Build sysparm_query query_parts = [] if validated_params.state: query_parts.append(f"state={validated_params.state}") if validated_params.application: query_parts.append(f"application={validated_params.application}") if validated_params.developer: query_parts.append(f"developer={validated_params.developer}") if validated_params.timeframe: if validated_params.timeframe == "recent": query_parts.append("sys_created_onONLast 7 days@javascript:gs.beginningOfLast7Days()@javascript:gs.endOfToday()") elif validated_params.timeframe == "last_week": query_parts.append("sys_created_onONLast week@javascript:gs.beginningOfLastWeek()@javascript:gs.endOfLastWeek()") elif validated_params.timeframe == "last_month": query_parts.append("sys_created_onONLast month@javascript:gs.beginningOfLastMonth()@javascript:gs.endOfLastMonth()") if validated_params.query: query_parts.append(validated_params.query) if query_parts: query_params["sysparm_query"] = "^".join(query_parts) # Make the API request url = f"{instance_url}/api/now/table/sys_update_set" try: response = requests.get(url, params=query_params, headers=headers) response.raise_for_status() result = response.json() return { "success": True, "changesets": result.get("result", []), "count": len(result.get("result", [])), } except requests.exceptions.RequestException as e: logger.error(f"Error listing changesets: {e}") return { "success": False, "message": f"Error listing changesets: {str(e)}", }
  • Pydantic BaseModel defining the input schema/parameters for the list_changesets tool, used to generate MCP inputSchema.
    class ListChangesetsParams(BaseModel): """Parameters for listing changesets.""" limit: Optional[int] = Field(10, description="Maximum number of records to return") offset: Optional[int] = Field(0, description="Offset to start from") state: Optional[str] = Field(None, description="Filter by state") application: Optional[str] = Field(None, description="Filter by application") developer: Optional[str] = Field(None, description="Filter by developer") timeframe: Optional[str] = Field(None, description="Filter by timeframe (recent, last_week, last_month)") query: Optional[str] = Field(None, description="Additional query string")
  • MCP tool registration: maps 'list_changesets' to its handler (list_changesets_tool), schema (ListChangesetsParams), description, etc., in the tool_definitions dict loaded by the server.
    "list_changesets": ( list_changesets_tool, ListChangesetsParams, str, # Expects JSON string "List changesets from ServiceNow", "json", # Tool returns list/dict ),
  • Imports list_changesets from changeset_tools.py into the tools package namespace, enabling its use in tool_utils.py.
    from servicenow_mcp.tools.changeset_tools import ( add_file_to_changeset, commit_changeset, create_changeset, get_changeset_details, list_changesets, publish_changeset, update_changeset, )
  • Helper function to unwrap dictionary or Pydantic model params, validate against schema, and check required fields. Used by list_changesets.
    def _unwrap_and_validate_params( params: Union[Dict[str, Any], BaseModel], model_class: Type[T], required_fields: Optional[List[str]] = None ) -> Dict[str, Any]: """ Unwrap and validate parameters. Args: params: The parameters to unwrap and validate. Can be a dictionary or a Pydantic model. model_class: The Pydantic model class to validate against. required_fields: List of fields that must be present. Returns: A dictionary with success status and validated parameters or error message. """ try: # Handle case where params is already a Pydantic model if isinstance(params, BaseModel): # If it's already the correct model class, use it directly if isinstance(params, model_class): model_instance = params # Otherwise, convert to dict and create new instance else: model_instance = model_class(**params.dict()) # Handle dictionary case else: # Create model instance model_instance = model_class(**params) # Check required fields if required_fields: missing_fields = [] for field in required_fields: if getattr(model_instance, field, None) is None: missing_fields.append(field) if missing_fields: return { "success": False, "message": f"Missing required fields: {', '.join(missing_fields)}", } return { "success": True, "params": model_instance, } except Exception as e: return { "success": False, "message": f"Invalid parameters: {str(e)}", }

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