Data Exploration

by reading-plus-ai

544 stars

678 downloads

Not rated

GitHub

About

MCP server for autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Details

Author: reading-plus-ai
GitHub stars: 544
Downloads: 678
Categories: Database, Community, Other, Search

- Pre-built explore-data prompt template for data exploration.
- Tools to load CSV files and execute Python scripts.
- Handles large datasets (e.g., 2.2 million entries, 178.9 MB).
- Generates visualizations and summary reports.
- Open source under the MIT License.
- Contributed by ReadingPlus.AI LLC.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Data Exploration

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

From the repository

Download Claude Desktop, then run python setup.py on macOS. After the server loads, select the explore-data prompt template and provide a local CSV file path and a topic of exploration. Configure the server in Claude Desktop’s claude_desktop_config.json using the provided mcpServers block.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "data exploration": {
            "mcp-server-data-exploration": {
                "command": "python",
                "args": [
                    "setup.py"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-server-data-exploration": {
        "command": "python",
        "args": [
            "setup.py"
        ]
    }
}

# 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. <a href="https://glama.ai/mcp/servers/hwm8j9c422"><img width="380" height="200" src="https://glama.ai/mcp/servers/hwm8j9c422/badge" alt="mcp-server-data-exploration MCP server" /></a> ## 🚀 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 [![Watch the video](https://img.youtube.com/vi/RQZbeuaH9Ys/hqdefault.jpg)](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) <img width="1622" alt="Screenshot 2024-12-09 at 12 48 56 AM" src="https://github.com/user-attachments/assets/9e70fe97-8af7-4221-b1e7-00197c88bb47"> - [Temperature-Humidity Relationship by Season](https://claude.site/artifacts/32a3371c-698d-48e3-b94e-f7e88ce8093d) <img width="1623" alt="Screenshot 2024-12-09 at 12 47 54 AM" src="https://github.com/user-attachments/assets/f4ac60a8-30e3-4b10-b296-ba412c2922fa"> - [Wind Direction Pattern by Season](https://claude.site/artifacts/32a3371c-698d-48e3-b94e-f7e88ce8093d) <img width="1622" alt="Screenshot 2024-12-09 at 12 47 00 AM" src="https://github.com/user-attachments/assets/2db01054-f948-4d2e-ba39-8de8fa59f83d"> ## 📦 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 provided 2. **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.

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Install

More like this

Sequential Thinking

Redis

Filesystem

EverArt

Google Drive

Sqlite