ServiceNow MCP Server

Instructions

Implementation Reference

• src/servicenow_mcp/tools/changeset_tools.py:192-284 (handler)

  The core handler function that implements the logic for listing changesets. It validates input parameters, constructs the appropriate ServiceNow Table API query for the sys_update_set table, makes the HTTP GET request, and returns the results or error.

  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)}",
          }

• src/servicenow_mcp/tools/changeset_tools.py:22-32 (schema)

  Pydantic BaseModel defining the input schema for the list_changesets tool, including optional filters like limit, offset, state, application, developer, timeframe, and custom query.

  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")

• src/servicenow_mcp/utils/tool_utils.py:621-627 (registration)

  Tool registration entry in get_tool_definitions() function, mapping the tool name to its handler (list_changesets_tool), input schema model (ListChangesetsParams), return type hint, description, and serialization instruction. This dictionary is used by the MCP server to expose the tool and handle calls.

  "list_changesets": (
      list_changesets_tool,
      ListChangesetsParams,
      str,  # Expects JSON string
      "List changesets from ServiceNow",
      "json",  # Tool returns list/dict
  ),

• src/servicenow_mcp/tools/changeset_tools.py:81-133 (helper)

  Helper function used by the handler to unwrap dictionary parameters into a Pydantic model instance, validate them, and check for required fields. Called at the start of 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)}",
          }