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

Your personal Data Scientist assistant, turning complex datasets into clear, actionable insights.

1. Download Claude Desktop

   • Get it here

2. Install and Set Up

   • On macOS, run the following command in your terminal:

   python setup.py

3. Load Templates and Tools

   • Once the server is running, wait for the prompt template and tools to load in Claude Desktop.

4. Start Exploring

   • Select the explore-data prompt template from MCP
   • Begin your conversation by providing the required inputs:
     • csv_path: Local path to the CSV file
     • topic: The topic of exploration (e.g., "Weather patterns in New York" or "Housing prices in California")

These are examples of how you can use MCP Server to explore data without any human intervention.

• Kaggle Dataset: USA Real Estate Dataset
• Size: 2,226,382 entries (178.9 MB)
• Topic: Housing price trends in California

• Data Exploration Summary

• Kaggle Dataset: 2M+ Daily Weather History UK
• Size: 2,836,186 entries (169.3 MB)
• Topic: Weather in London
• Report: View Report
• Graphs:
  • London Temperature Trends

• Temperature-Humidity Relationship by Season

• Wind Direction Pattern by Season

• explore-data: Tailored for data exploration tasks

1. load-csv

   • Function: Loads a CSV file into a DataFrame
   • Arguments:
     • csv_path (string, required): Path to the CSV file
     • df_name (string, optional): Name for the DataFrame. Defaults to df_1, df_2, etc., if not provided

2. run-script

   • Function: Executes a Python script
   • Arguments:
     • script (string, required): The script to execute

• macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%/Claude/claude_desktop_config.json

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

"mcpServers": {
  "mcp-server-ds": {
    "command": "uvx",
    "args": [
      "mcp-server-ds"
    ]
  }
}

1. Sync Dependencies

   uv sync

2. Build Distributions

   uv build

   Generates source and wheel distributions in the dist/ directory.

3. Publish to PyPI

   uv publish

Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.

If you encounter bugs or have suggestions, open an issue in the issues section. Include:

• Steps to reproduce (if applicable)
• Expected vs. actual behavior
• Screenshots or error logs (if relevant)

This project is licensed under the MIT License. See the LICENSE file for details.

Questions? Feedback? Open an issue or reach out to the maintainers. Let's make this project awesome together!

This is an open source project run by ReadingPlus.AI LLC. and open to contributions from the entire community.