Optuna MCP Server

Official

MIT License

Overview InspectNew Endpoints Schema Related Servers Reviews Score

set_sampler

Configure the sampler for optimization studies on the Optuna MCP Server. Choose from TPESampler, NSGAIISampler, RandomSampler, or GPSampler to define the sampling strategy based on study objectives.

Instructions

Set the sampler for the study. The sampler must be one of the following: - TPESampler - NSGAIISampler - RandomSampler - GPSampler

    The default sampler for single-objective optimization is TPESampler.
    The default sampler for multi-objective optimization is NSGAIISampler.
    GPSampler is a Gaussian process-based sampler suitable for low-dimensional numerical optimization problems.
    

Input Schema

Name	Required	Description	Default
`name`	Yes

Input Schema (JSON Schema)

{
  "properties": {
    "name": {
      "enum": [
        "TPESampler",
        "NSGAIISampler",
        "RandomSampler",
        "GPSampler"
      ],
      "title": "Name",
      "type": "string"
    }
  },
  "required": [
    "name"
  ],
  "title": "set_samplerArguments",
  "type": "object"
}

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/optuna/optuna-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server