Linear Regression MCP

🚀 Linear Regression MCP Project

This project demonstrates an end-to-end machine learning workflow using Claude and the Model Context Protocol (MCP). By uploading a CSV file, Claude can independently train a linear regression model, covering the entire lifecycle of machine learning model training, including data preprocessing, training, and evaluation (calculating RMSE).

🚀 Quick Start

✨ Features

This project showcases an end - to - end machine learning workflow with Claude and MCP. It enables independent training of a linear regression model by simply uploading a CSV file, handling all aspects of the machine learning model training lifecycle.

📦 Installation

1. Clone the repository:

First, clone the repository to your local machine:

git clone https://github.com/HeetVekariya/Linear-Regression-MCP
cd Linear-Regression-MCP

2. Install uv:

uv is an ultra - fast Python package and project manager written in Rust. It is required for server management and dependency management in this project.

• Download and install uv from here.

3. Install dependencies:

Once uv is installed, run the following command to install all necessary dependencies:

uv sync

4. Configure Claude Desktop:

To integrate the server with Claude Desktop, you need to modify Claude's configuration file. Do the following based on your operating system:

• For macOS or Linux:

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

• For Windows:

code $env:AppData/Claude/claude_desktop_config.json

• Find the mcpServers section in the configuration file and replace the placeholder paths with the absolute path of the uv installation and the linear regression project directory. It should look like this:

{
    "mcpServers":
    {
        "linear-regression": 
        {
            "command": "ABSOLUTE/PATH/TO/.local/bin/uv",
            "args":
            [
                "--directory",
                "ABSOLUTE/PATH/TO/YOUR-LINEAR-REGRESSION-REPO", 
                "run",
                "server.py"
            ] 
        }
    }
}

• After saving the file, restart Claude Desktop to link to the MCP server.

💻 Usage Examples

Available Tools

The following tools are available for this project to help you process datasets and train models:

🤝 Contribution

We welcome contributions from the community! If you have any questions, suggestions, or improvements, please visit the GitHub repository to submit an issue or a pull request.

📞 Contact

If you need to contact the project maintainers or get more support, please reach out to us through the following channels:

Email | GitHub | Dev.to | Medium

Thank you for using the Linear Regression MCP project! We look forward to your participation and feedback.