MCP Server for Data Exploration
LocalAbout MCP Server for Data Exploration
MCP Server for Data Exploration is an MCP server for interactive exploration of CSV datasets. It is aimed at users who want quick summaries and charts from local data, and it provides an explore-data prompt template alongside loading and script tools.
Key features
- 01Load CSV files into DataFrames
- 02Run Python scripts
- 03Provide an explore-data prompt template
- 04Set optional DataFrame names
Use cases
- 01Run exploratory analysis on local CSV datasets
- 02Generate a topic-based data exploration summary with graphs
MCP support
This project is an MCP server that exposes the load-csv and run-script tools and the explore-data prompt template to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP 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 filetopic: 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
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 filedf_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 buildGenerates 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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
