# reading-plus-ai/mcp-server-data-exploration [Health: Active]

**Category:** 🧮 Data Science Tools  
**Repository:** https://github.com/reading-plus-ai/mcp-server-data-exploration  
**GitHub Stars:** 544  
**Views:** 2  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/reading-plus-ai-mcp-server-data-exploration

## Description
Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

## Tools
Capabilities this server exposes over MCP:

- **csv_path**
- **df_name**
- **script**

## Claude Desktop Quick Installation
No confirmed install details yet, so no config is published. Follow the setup steps in the repository above.

## Documentation

## What reading-plus-ai/mcp-server-data-exploration does

The reading-plus-ai/mcp-server-data-exploration MCP server supports interactive exploration of local CSV datasets through MCP. It is listed in the 🧮 Data Science Tools category and is intended for analysis tasks where an AI assistant can inspect data, propose lines of inquiry, and produce findings from a stated topic.

The repository provides an `explore-data` prompt template. A conversation using that prompt requires a local `csv_path` and a `topic`, such as weather patterns in New York or housing prices in California. The examples describe analyses of large real-estate and weather-history CSV files, including reports, trends, and graphs.

## How it works

The server exposes two documented tools. `load-csv` reads a CSV file into a DataFrame. It accepts the required `csv_path` string and an optional `df_name`; when no name is supplied, the server uses names such as `df_1` and `df_2`.

`run-script` executes a supplied Python script. Together, these tools let an MCP client load one or more datasets and run Python-based exploration against the resulting DataFrames. The prompt template provides the interaction pattern, while the tools provide file loading and script execution.

## Setup and configuration

The documented quick-start path uses Claude Desktop. On macOS, the README instructs users to run `python setup.py`, start the server, and wait for the prompt template and tools to appear. The reading-plus-ai/mcp-server-data-exploration MCP server can then be selected through the `explore-data` prompt.

Claude Desktop configuration files are located at `~/Library/Application Support/Claude/claude_desktop_config.json` on macOS and `%APPDATA%/Claude/claude_desktop_config.json` on Windows. The repository shows an unpublished-server configuration using `uv --directory ... run mcp-server-ds` and a published-server configuration using `uvx mcp-server-ds`.

## Tools and capabilities

- Load a local CSV into a DataFrame.
- Assign an optional DataFrame name or use an automatic default.
- Execute Python analysis scripts.
- Explore data through the `explore-data` prompt.
- Supply a topic to focus the exploration.

## Limitations and notes

The documented input format is CSV, and the examples use local file paths. The reading-plus-ai/mcp-server-data-exploration MCP server requires a client that supports its prompt and tools; the README specifically documents Claude Desktop. Python scripts are executed by the server, so deployments should consider the contents and permissions of scripts supplied to it. The repository does not document database connectors, remote dataset storage, authentication settings, or environment variables.

_Full upstream README: https://allmcps.com/mcp/reading-plus-ai-mcp-server-data-exploration/readme_