How do I install the optuna mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

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Optuna MCP Server

The Optuna MCP Server can be used in the following use cases, for example.

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What is the Optuna MCP Server?

The Optuna MCP Server can be used in the following use cases, for example.

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

Tool	What it does
create_study	Create a new Optuna study with the given study_name and directions.
study_name	name of the study (string, required).
directions	The directions of optimization (list of literal strings minimize/maximize, optional).
set_sampler	Set the sampler for the study.
get_all_study_names	Get all study names from the storage.
set_metric_names	Set metric_names. Metric_names are labels used to distinguish what each objective value is.
metric_names	The list of metric names for each objective (list of strings, required).
get_metric_names	Get metric_names.
get_directions	Get the directions of the study.
get_trials	Get all trials in a CSV format.
best_trial	Get the best trial.
best_trials	Return trials located at the Pareto front in the study.
ask	Suggest new parameters using Optuna.
search_space	the search space for Optuna (dictionary, required).
tell	Report the result of a trial.
trial_number	the trial number (integer, required).
values	the result of the trial (float or list of floats, required).
set_trial_user_attr	Set user attributes for a trial.
key	the key of the user attribute (string, required).
value	the value of the user attribute (any type, required).
get_trial_user_attrs	Get user attributes in a trial.
plot_optimization_history	Return the optimization history plot as an image.
target	an index to specify the value to display (integer, required).
target_name	target’s name to display on the color bar (string, required).
plot_hypervolume_history	Return the hypervolume history plot as an image.
reference_point	a list of reference points to calculate the hypervolume (list of floats, required).
plot_pareto_front	Return the Pareto front plot as an image for multi-objective optimization.
target_names	objective name list used as the axis titles (list of strings, optional).
include_dominated_trials	a flag to include all dominated trial's objective values (boolean, optional).
targets	a list of indices to specify the objective values to display. (list of integers, optional).
plot_contour	Return the contour plot as an image.
params	parameter list to visualize (list of strings, optional).
plot_parallel_coordinate	Return the parallel coordinate plot as an image.
plot_slice	Return the slice plot as an image.
plot_param_importances	Return the parameter importances plot as an image.
plot_edf	Return the EDF plot as an image.
plot_timeline	Return the timeline plot as an image.
plot_rank	Return the rank plot as an image.
launch_optuna_dashboard	Launch the Optuna dashboard.
port	server port (integer, optional, default: 58080).

How to install the Optuna MCP Server

{
  "mcpServers": {
    "Optuna": {
      "command": "/path/to/uvx",
      "args": [
        "optuna-mcp"
      ]
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Example prompts to try

“Use Optuna MCP to Study.”
“Use Optuna MCP to Trial.”
“Use Optuna MCP to Visualization.”

Frequently asked questions

The Optuna MCP Server can be used in the following use cases, for example. Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.