MCP Server for Data Exploration

Provides an MCP server enabling interactive data exploration from CSV sources using prompts and built-in tools.

python

0

GitHub Stars

python

Language

4 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "mcp-mirror-reading-plus-ai_mcp-server-data-exploration": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/username/src/mcp-server-ds",
        "run",
        "mcp-server-ds"
      ]
    }
  }
}

MCP Server for Data Exploration provides an interactive environment to explore datasets using prompts and built-in tools. It lets you load CSV data, run Python scripts, and generate actionable insights through a guided, prompt-driven experience.

How to use

You use this MCP server with an MCP client to explore data interactively. Start the server in stdio mode, then load CSV data and execute exploration prompts. You can point the server at a local CSV file, choose a topic for analysis, and receive structured data-driven insights, summaries, and visualizations through the client interface.

How to install

Prerequisites: ensure Python is installed on your system. You will run a local setup to initialize the MCP server environment.

Step 1: Open a terminal or command prompt.

Step 2: Run the setup command to install and configure the server components.

python setup.py

Configuration and run modes

Two local, self-contained MCP server configurations are provided for development and testing. Each runs the MCP server as a stdio process. You can choose either depending on your workflow.

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

If you prefer the published form, you can run the same server via the published entry:

"mcpServers": {
  "mcp_server_ds": {
    "command": "uvx",
    "args": [
      "mcp-server-ds"
    ]
  }
}

Additional details

After starting, wait for the server to load the prompt templates and tools. Then in your MCP client, select the explore-data prompt template and provide inputs such as the path to your CSV file and the exploration topic.

Examples and tools

The server exposes specific tools to help you work with data: load-csv and run-script.

Troubleshooting tips

If the server does not start or fail to load prompts, ensure the directory paths in the configuration exist and that Python is accessible from your terminal. Check that you have a CSV file ready for loading and that your MCP client is connected to the correct server instance.

Tools and capabilities

load-csv: 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.
run-script: Executes a Python script. Arguments: script (string, required): the script to execute.

Notes on environment and tooling

Environment and execution are managed locally via the MCP server runtime. No external MCP endpoints are required unless you configure them separately in your environment.

Available tools

load-csv

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.

run-script

Executes a Python script. Arguments: script (string, required): the script to execute.