Quick Data for Windows MCP

Quick Data for Windows MCP is an MCP server that provides universal data analytics and visualization capabilities on Windows systems for Claude Desktop. It acts as a local data processing bridge connecting AI assistants directly to CSV and JSON files on a user's Windows machine. Data analysts, developers, and Windows users utilize this server to inspect tabular and structured datasets without encountering path resolution issues or environment mismatches. Built as a Windows-adapted fork of the original quick-data-mcp project, it manages proper absolute path parsing and automated dependency management via Windows batch scripts. The server exposes over 32 analytics tools covering automated schema discovery, categorical segmentation, outlier detection, distribution analysis, and correlation modeling. It also allows Claude Desktop to generate interactive Plotly charts, assess overall dataset quality scores, compare disparate data structures, and merge multiple files directly in memory.

Category: Data & Analytics

Tags: csv, data analysis, json, windows

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How to install and configure Quick Data for Windows MCP

1. Clone the repository using Git: git clone https://github.com/Beaulewis1977/quick-data-for-windows-mcp.git and open the directory: cd quick-data-for-windows-mcp. 2. Install dependencies by running the automated batch script: install_dependencies.bat. 3. Test the local server execution: test_server.bat. 4. Copy the sample configuration file to Claude Desktop: copy claude_desktop_config_fixed.json "%APPDATA%\Claude\claude_desktop_config.json". 5. Edit %APPDATA%\Claude\claude_desktop_config.json to update the cwd, main.py path, and PYTHONPATH to your actual installation directory. 6. Restart Claude Desktop and initialize using /quick-data-windows.

What you can do with Quick Data for Windows MCP

• Load local CSV or JSON datasets into Claude Desktop using absolute Windows file paths with automatic schema detection. - Calculate statistical distributions, identify numerical outliers, and find variable correlations within loaded tabular datasets. - Create interactive Plotly visualizations such as bar charts, scatter plots, line charts, and multi-chart dashboards. - Validate data quality scores and clean up duplicate records across complex or nested JSON and CSV files. - Merge multiple local datasets together and compute machine learning feature importance using built-in scikit-learn tools.

Key facts

• https://github.com/Beaulewis1977/quick-data-for-windows-mcp
• Data & Analytics, Files, Documents & PDFs
• csv, data analysis, json, windows

Part of MCP Servers

What is Quick Data for Windows MCP?

Quick Data for Windows MCP is a Windows-optimized Model Context Protocol server that enables Claude Desktop to run statistical analytics, discover schemas, and build interactive Plotly charts from local CSV and JSON files.

How do I install Quick Data for Windows MCP?

Clone the repository from GitHub, run the install_dependencies.bat batch script, test the server using test_server.bat, and update your Claude Desktop configuration file with the exact local paths before restarting the client application.

Which MCP clients work with Quick Data for Windows MCP?

This server is pre-configured and optimized specifically for Claude Desktop on Windows 10 and 11, though it runs via standard input and output and can connect to other standard MCP-compatible clients.

Is Quick Data for Windows MCP open source?

Yes, Quick Data for Windows MCP is open source and distributed under the MIT License, which is maintained from the original project repository.