Data Exploration

by reading-plus-ai

544 678 downloads Not rated yet

GitHub

About

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

Explore

- 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

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

`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

`script`

(string, required): The script to execute

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

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.

🚀 Try it Out

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")

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: - London Temperature Trends Screenshot 2024-12-09 at 12 48 56 AM

- Temperature-Humidity Relationship by Season
Screenshot 2024-12-09 at 12 47 54 AM

- Wind Direction Pattern by Season
Screenshot 2024-12-09 at 12 47 00 AM

📦 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)

"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

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

🤝 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.

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About

Explore

Setting up with Highlight

From the repository

csv_path

df_name

script

Claude Desktop / Cursor

McpServers

MCP Server for Data Exploration

🚀 Try it Out

Examples

Case 1: California Real Estate Listing Prices

Case 2: Weather in London

📦 Components

Prompts

Tools

⚙️ Modifying the Server

Claude Desktop Configurations

Development (Unpublished Servers)

Published Servers

🛠️ Development

Building and Publishing

🤝 Contributing

Reporting Issues

📜 License

💬 Get in Touch

About

Videos about Data Exploration

How to Integrate MongoDB with Cursor and MCP Server Seamlessly | Complete Setup Tutorial

“AI-Driven Data Exploration: Autonomous Insights with Claude 3.5 and MCP Server

Using MCP with FME for Data Exploration

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`csv_path`

`df_name`

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