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

Overview

This is a Model Context Protocol server for Scikit-learn, providing a standardized interface for interacting with Scikit-learn models and datasets.

Related MCP server: HistGradientBoostingClassifier MCP Server

Features

• 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

Run this project locally

This project is not yet set up for ephemeral environments (e.g. uvx usage). Run this project locally by cloning this repo:

git clone https://github.com/yourusername/mcp-server-scikit-learn.git
cd mcp-server-scikit-learn

You can launch the MCP inspector via npm:

npx @modelcontextprotocol/inspector uv --directory=src/mcp_server_scikit_learn run mcp-server-scikit-learn

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

OR Add this tool as a MCP server:

{
  "scikit-learn": {
    "command": "uv",
    "args": [
      "--directory",
      "/path/to/mcp-server-scikit-learn",
      "run",
      "mcp-server-scikit-learn"
    ]
  }
}

Development

1. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

2. Install dependencies:

pip install -e ".[dev]"

3. Run tests:

pytest -s -v tests/

License