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mcp-server-scikit-learn: MCP server for Scikit-learn

@shibuiwilliam

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT license

トランスポート

stdio

作者

shibuiwilliam

mcp-server-scikit-learn: MCP server for Scikit-learn について

概要はまだありません

#mcp-server#scikit-learn#model-context-protocol

mcp-server-scikit-learn: MCP server for Scikit-learn の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-server-scikit-learn": {
      "command": "npx",
      "args": [
        "@modelcontextprotocol/inspector",
        "uv",
        "--directory=src/mcp_server_scikit_learn",
        "run",
        "mcp-server-scikit-learn"
      ]
    }
  }
}

mcp-server-scikit-learn: MCP server for Scikit-learn のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is mcp-server-scikit-learn?

The mcp-server-scikit-learn is a Model Context Protocol server that provides a standardized interface for interacting with Scikit-learn models and datasets. It is designed for developers who want to train, evaluate, and manage Scikit-learn models via the MCP protocol.

How to use mcp-server-scikit-learn?

Clone the repository locally, then launch the MCP inspector using npx @modelcontextprotocol/inspector uv --directory=src/mcp_server_scikit_learn run mcp-server-scikit-learn. Alternatively, add it as a MCP server in your configuration with the uv command pointing to the local directory.

Key features of mcp-server-scikit-learn

  • Train and evaluate Scikit-learn models
  • Handle datasets and data preprocessing
  • Model persistence and loading
  • Feature engineering and selection
  • Model evaluation metrics
  • Cross-validation and hyperparameter tuning

Use cases of mcp-server-scikit-learn

  • Train and evaluate machine learning models through an MCP-compliant interface
  • Automate data preprocessing and feature engineering pipelines
  • Manage model lifecycle with persistent storage and loading
  • Perform cross-validation and hyperparameter tuning remotely

よくある質問

1

Is this server ready for ephemeral environments like `uvx`?

No, this project is not yet set up for ephemeral environments; you must clone the repo and run it locally.

2

What are the runtime requirements?

The server requires Python and uses `uv` as the package runner; a virtual environment is recommended.

3

How do I debug the server?

Launch the MCP inspector via npm (`npx @modelcontextprotocol/inspector ...`) to get a browser-accessible debugging URL.

4

Can I use this server without cloning the repo?

Currently, a local clone is required; there is no `uvx` or pip-based one-line install described in the README.

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