MCP Data Analyst

MCP Data Analyst

Enables AI clients to perform data analysis on CSV datasets through tools for dataset info, summaries, missing value detection, regional sales filtering, and column statistics.

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README

MCP Data Analyst

A lightweight Model Context Protocol (MCP) server built with Python and Pandas that exposes reusable data-analysis capabilities as MCP tools.

Overview

This project demonstrates how an MCP-compatible client can discover and invoke external data-analysis tools through a standardized MCP server.

The server analyzes a sample sales CSV dataset and exposes five tools:

  • dataset_info - Returns dataset dimensions and column names
  • dataset_summary - Returns descriptive statistics
  • missing_values - Detects missing values
  • sales_by_region - Filters sales records by region
  • column_analysis - Calculates statistics for numeric columns

Architecture

User / AI Host | v MCP Client | v MCP Server | v MCP Tools | v Python + Pandas | v Sales CSV Dataset

Project Structure

mcp-data-analyst/ ├── data/ │ └── sample_sales.csv ├── tests/ │ └── test_analysis.py ├── tools/ │ ├── init.py │ ├── analysis_tools.py │ └── csv_tools.py ├── server.py ├── requirements.txt ├── pytest.ini ├── .gitignore └── README.md

Technologies

  • Python
  • Model Context Protocol (MCP)
  • Pandas
  • Pytest
  • MCP Inspector

Installation

Create and activate a virtual environment.

Windows PowerShell:

python -m venv venv
.\venv\Scripts\Activate.ps1

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