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Linear Regression

heetvekariya/linear-regression-mcp

Welcome to Linear Regression MCP! This project demonstrates an end-to-end machine learning workflow using Claude and the Model Context Protocol (MCP).

Install

Client configuration

{
  "mcpServers": {
    "linear-regression": {
      "command": "ABSOLUTE/PATH/TO/.local/bin/uv",
      "args": [
        "--directory",
        "<value>",
        "run",
        "server.py"
      ]
    }
  }
}
GitHub stars
8
Category
Research & Data, Developer Tools
Updated
Oct 6, 2026

About Linear Regression

Claude can train a Linear Regression model entirely by itself, simply by uploading a CSV file containing the dataset. The system goes through the entire ML model training lifecycle, handling data preprocessing, training, and evaluation (RMSE calculation).

Tools (3)

  • get_columns_info

    Retrieves the column names in the uploaded dataset.

  • check_category_columns

    Checks for any categorical columns in the dataset.

  • label_encode_categorical_columns

    Label encodes categorical columns into numerical values.

Details on this page are taken from the project's README. Open README

Supported clients

Clients mentioned in this server's README:

View all
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Claude Desktop

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