https://github.com/reading-plus-ai/mcp-server-data-exploration
https://github.com/reading-plus-ai/mcp-server-data-exploration
Last synced: 29 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/reading-plus-ai/mcp-server-data-exploration
- Owner: reading-plus-ai
- License: mit
- Created: 2024-12-06T18:26:04.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-03-22T17:26:01.000Z (about 2 months ago)
- Last Synced: 2025-04-02T04:06:01.737Z (about 1 month ago)
- Language: Python
- Size: 43.9 KB
- Stars: 198
- Watchers: 2
- Forks: 23
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-mcp-zh - Data Exploration
- awesome-mcp-list - @reading-plus-ai/mcp-server-data-exploration - plus-ai/mcp-server-data-exploration?style=social)](https://github.com/reading-plus-ai/mcp-server-data-exploration): Enables autonomous data exploration on `.csv`-based datasets. (Uncategorized / Uncategorized)
- awesome-mcp-servers - @reading-plus-ai/mcp-server-data-exploration - Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort. (Legend / 🧮 Data Science Tools)
- awesome-mcp-servers - @reading-plus-ai/mcp-server-data-exploration - Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort. (Legend / 🧮 Data Science Tools)
- awesome-mcp-servers - Data Exploration - MCP server for autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort. (Community Servers)
- awesome-mcp-servers - Data Exploration - MCP server for autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort. (Community Servers)
- Awesome-MCP-Servers-directory - Data Exploration - MCP server for autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort (Data Science Tools)
- awesome-mcp-servers - Data Explorer Assistant - Generates actionable insights from complex datasets through interactive exploration (Table of Contents / Data Science Tools)
README
# 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
1. **Download Claude Desktop**
- Get it [here](https://claude.ai/download)2. **Install and Set Up**
- On macOS, run the following command in your terminal:
```bash
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")## 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](https://www.kaggle.com/datasets/ahmedshahriarsakib/usa-real-estate-dataset)
- Size: 2,226,382 entries (178.9 MB)
- Topic: Housing price trends in California[](https://www.youtube.com/watch?v=RQZbeuaH9Ys)
- [Data Exploration Summary](https://claude.site/artifacts/058a1593-7a14-40df-bf09-28b8c4531137)### Case 2: Weather in London
- Kaggle Dataset: [2M+ Daily Weather History UK](https://www.kaggle.com/datasets/jakewright/2m-daily-weather-history-uk/data)
- Size: 2,836,186 entries (169.3 MB)
- Topic: Weather in London
- Report: [View Report](https://claude.site/artifacts/601ea9c1-a00e-472e-9271-3efafb8edede)
- Graphs:
- [London Temperature Trends](https://claude.site/artifacts/9a25bc1e-d0cf-498a-833c-5179547ee268)- [Temperature-Humidity Relationship by Season](https://claude.site/artifacts/32a3371c-698d-48e3-b94e-f7e88ce8093d)
- [Wind Direction Pattern by Season](https://claude.site/artifacts/32a3371c-698d-48e3-b94e-f7e88ce8093d)
## 📦 Components
### Prompts
- **explore-data**: Tailored for data exploration tasks### Tools
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 provided2. **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)
```json
"mcpServers": {
"mcp-server-ds": {
"command": "uv",
"args": [
"--directory",
"/Users/username/src/mcp-server-ds",
"run",
"mcp-server-ds"
]
}
}
```### Published Servers
```json
"mcpServers": {
"mcp-server-ds": {
"command": "uvx",
"args": [
"mcp-server-ds"
]
}
}
```## 🛠️ Development
### Building and Publishing
1. **Sync Dependencies**
```bash
uv sync
```2. **Build Distributions**
```bash
uv build
```
Generates source and wheel distributions in the dist/ directory.3. **Publish to PyPI**
```bash
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](https://readingplus.ai). and open to contributions from the entire community.