MCP Server Data Exploration

🚀 MCP Server for Data Exploration

MCP Server is a powerful tool designed for interactive data exploration.

Your personal data scientist assistant, it transforms complex datasets into clear and actionable insights.

🚀 Quick Start

1. Download the Claude Desktop Version

   • Download link: Here

2. Installation and Setup

   • On macOS, run the following command:

     python setup.py
     

3. Load Templates and Tools

   • After the setup is complete, add the following content to the MCP Server:

     "mcp-servers": {
       "mcp-server-ds": {
         "command": "uv",
         "args": [
           "--directory",
           "/Users/username/src/mcp-server-ds",
           "run",
           "mcp-server-ds"
         ]
       }
     }
     

   • Restart the Claude desktop version to apply the changes.

4. Start Using

   run-script --script "print('Hello, MCP Server!')"
   

💻 Usage Examples

Basic Usage

• Load Data

  load data using the `load_script` function.
  

• Execute Script

  runSCRIPT --script "your_script.py"
  

Advanced Usage

Case 1: Basic Data Processing

import pandas as pd

# Load data
data = load_data(csv_path="your_data.csv")

# View data summary
print(data.head())

Case 2: Complex Data Analysis

from advanced_module import analyze_data

# Perform analysis
result = analyze_data(data)

# Visualize results
plot_results(result)

🛠️ Development and Contribution

Project Structure

mcp-server-ds/
├── server.py          # Main server file
├── scripts/          # Directory for executable scripts
│   └── your_script.py
└── config/           # Location for configuration files
    └── settings.json

Contribution Guidelines

How to Submit a Fix

1. Report an Issue

   • When submitting an issue, please provide the following information:
     • Steps to reproduce (if applicable)
     • Comparison between expected and actual behavior
     • Screenshots or error logs (if relevant)

2. Create a Branch

   git checkout -b feature/your-feature-name
   

3. Commit Code

   • Make sure to add all modified files:

     git add .
     

   • Commit the changes:

     git commit -m "Your commit message"
     

4. Submit a Pull Request

   • Open a Pull Request on GitHub and describe the modifications in the description.

How to Add a New Feature

1. Discuss Feasibility

   • Propose your idea in the Issues section or Discussions and consult with the maintainers.

2. Implement the Feature

   • Ensure that the code follows the project's coding standards.
   • Add corresponding documentation and test cases.

3. Submit a Pull Request

   • Provide a detailed description of the new feature and its value.

📄 License

This project is open - source under the MIT License. For more details, please refer to the LICENSE file.

💬 Contact Us

If you have any questions or feedback, please use the Issues section or contact the maintainers. Let's make this project even more awesome together!

About

This project is maintained by ReadingPlus.AI LLC. Community contributions are welcome!