Data Exploration

What is mcp-server-data-exploration?

mcp-server-data-exploration is an MCP (Multi-Agent Collaboration Platform) server designed for autonomous data exploration on CSV-based datasets. It acts as a personal Data Scientist assistant, providing intelligent insights with minimal effort. It is important to note that this tool will execute arbitrary Python code on your machine, so use it with caution.

How to use mcp-server-data-exploration?

To use mcp-server-data-exploration, follow these steps:

Download Claude Desktop: Get it from here.
Install and Set Up: On macOS, run python setup.py in your terminal.
Load Templates and Tools: Once the server is running, wait for the prompt template and tools to load in Claude Desktop.
Start Exploring: Select the explore-data prompt template from MCP and provide 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").

Key Features of mcp-server-data-exploration

Autonomous Data Exploration: Provides intelligent insights from CSV datasets with minimal effort.
Integration with Claude Desktop: Seamlessly integrates with Claude Desktop for interactive use.
Prompt-driven Interaction: Uses the explore-data prompt for guided data analysis.
Tooling: Includes load-csv to load CSV files into DataFrames and run-script to execute Python scripts.
Customizable: Allows for modification of server configurations in Claude Desktop.
Open Source: Community-driven project with opportunities for contributions.

Use Cases of mcp-server-data-exploration

California Real Estate Listing Prices: Analyze large datasets (e.g., 2M+ entries) to understand housing price trends.
Weather Analysis: Explore weather patterns and generate reports and graphs (e.g., temperature trends, temperature-humidity relationships, wind direction patterns).
General Data Exploration: Any scenario requiring quick and intelligent insights from CSV data without manual coding.

FAQ from mcp-server-data-exploration

Q: What are the main components of the server? A: The server includes explore-data prompts for data exploration and tools like load-csv (to load CSVs) and run-script (to execute Python scripts).

Q: How can I modify the server configurations? A: You can modify configurations in claude_desktop_config.json located in ~/Library/Application\ Support/Claude/ on macOS or %APPDATA%/Claude/ on Windows.

Q: How can I contribute to the project? A: Contributions are welcome! You can report issues with steps to reproduce, expected vs. actual behavior, and relevant screenshots/logs. You can also contribute by fixing bugs, adding features, or improving documentation.

Q: What is the license for this project? A: This project is licensed under the MIT License. See the LICENSE file for details.

Q: Who is behind this project? A: This is an open-source project run by ReadingPlus.AI LLC and open to contributions from the entire community.

MCP Server for Data Exploration

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

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

🚀 Try it Out

Download Claude Desktop
- Get it here
Install and Set Up
- On macOS, run the following command in your terminal:
```
python setup.py
```
Load Templates and Tools
- Once the server is running, wait for the prompt template and tools to load in Claude Desktop.
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")

Examples

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

Case 1: California Real Estate Listing Prices

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

Data Exploration Summary

Case 2: Weather in London

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

📦 Components

Prompts

explore-data: Tailored for data exploration tasks

Tools

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

⚙️ Modifying the Server

Claude Desktop Configurations

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

Development (Unpublished Servers)

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

Published Servers

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

🛠️ Development

Building and Publishing

Sync Dependencies
```
uv sync
```
Build Distributions
```
uv build
```
Generates source and wheel distributions in the dist/ directory.
Publish to PyPI
```
uv publish
```

🤝 Contributing

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

Reporting Issues

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)

📜 License

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

💬 Get in Touch

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

About

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