Optuna MCP Server

Instructions

    Args:
        params:
            Parameter list to visualize. The default is all parameters.
        target:
            An index to specify the value to display. To plot nth objective value, set this to n.
            Note that this is 0-indexed, i.e., to plot the first objective value, set this to 0.
            By default, all objective will be plotted by setting target to None.
        target_name:
            Target’s name to display on the legend.
    

Implementation Reference

• optuna_mcp/server.py:557-583 (handler)

  The handler function implementing the plot_param_importances tool. It uses Optuna's visualization module to create a parameter importances plot with a PedAnova importance evaluator and returns the plot as a PNG image via the Image type.

  @mcp.tool()
  def plot_param_importances(
      params: list[str] | None = None,
      target: int | None = None,
      target_name: str = "Objective Value",
  ) -> Image:
      """Return the parameter importances plot as an image.
  
      Args:
          params:
              Parameter list to visualize. The default is all parameters.
          target:
              An index to specify the value to display. To plot nth objective value, set this to n.
              Note that this is 0-indexed, i.e., to plot the first objective value, set this to 0.
              By default, all objective will be plotted by setting target to None.
          target_name:
              Target’s name to display on the legend.
      """
      evaluator = optuna.importance.PedAnovaImportanceEvaluator()
      fig = optuna.visualization.plot_param_importances(
          mcp.study,
          evaluator=evaluator,
          params=params,
          target=(lambda t: t.values[target]) if target is not None else None,
          target_name=target_name,
      )
      return Image(data=plotly.io.to_image(fig), format="png")