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Linear Regression MCP

@HeetVekariya

リポジトリ

Linear Regression MCP について

MCP server for training Linear Regression Model.

#mcp#linear-regression#machine-learning

基本情報

カテゴリ

バージョン管理

ランタイム

python

トランスポート

stdio

公開者

HeetVekariya

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": {
    "Linear-Regression-MCP": {
      "command": "uv",
      "args": [
        "sync"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Linear Regression MCP?

Linear Regression MCP is a Model Context Protocol server that lets Claude train a linear regression model end-to-end by simply uploading a CSV file. It automates data preprocessing, training, and evaluation (RMSE calculation), making it ideal for users who want to run ML workflows through natural language.

How to use Linear Regression MCP?

Clone the repository, install uv, run uv sync, then configure Claude Desktop by adding the server path to claude_desktop_config.json. Once linked, Claude can invoke tools like upload_file, get_columns_info, and train_linear_regression_model.

Key features of Linear Regression MCP

  • End-to-end ML model training lifecycle with Claude.
  • Upload any CSV dataset for automatic processing.
  • Automatic categorical column label encoding.
  • RMSE-based evaluation after training.
  • Tools to inspect column info and data types.
  • Open-source and welcomes contributions.

Use cases of Linear Regression MCP

  • Train a linear regression model on a local CSV without writing code.
  • Rapidly prototype regression models using natural language instructions.
  • Automate data preprocessing and model evaluation for educational or small-scale projects.

FAQ from Linear Regression MCP

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コメント

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