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MCP Server for Data Exploration

Provides an interactive data exploration server that loads CSV data and runs Python scripts to generate insights.

Installation
Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "reading-plus-ai-mcp-server-data-exploration": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/username/src/mcp-server-ds",
        "run",
        "mcp-server-ds"
      ],
      "env": {
        "YOUR_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

MCP Server for Data Exploration lets you load CSV data and run Python-based scripts to derive insights through an interactive client. It provides prompts and lightweight tools to query datasets, generate summaries, and visualize patterns without writing boilerplate code.

How to use

You use an MCP client to connect to an MCP Server that is focused on data exploration. Start the client, choose the explore-data prompt template, and provide inputs like the path to your CSV file and a topic for exploration. The server loads the CSV into a DataFrame and exposes tools you can invoke to summarize, analyze correlations, or generate basic visual reports. You can iteratively refine your topic and inputs to drive deeper insights from your data.

How to install

Prerequisites: ensure Python is installed on your machine. You also need Claude Desktop if you plan to run the server through that client experience.

python setup.py

Additional configuration and notes

Configurable server snippets are shown for local and published MCP server setups. Use these directly if you are running an MCP server in development or in production environments.

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

Available tools

explore-data

Tailored prompt for data exploration tasks that coordinates data loading, analysis, and reporting.

load-csv

Loads a CSV file into a DataFrame for subsequent analysis.

run-script

Executes a Python script within the MCP environment.