md.it is a web application that bridges the gap between document processing and text analysis by providing a simple, intuitive interface for converting various document formats into clean, structured Markdown.
The project combines:
- MarkItDown - A lightweight Python utility for converting files to Markdown
- Flask - A lightweight web framework for the user interface
- PDF Processing Libraries - pypdf and pdfplumber for advanced PDF handling
The core goal of md.it is to make document-to-Markdown conversion accessible through a web interface, enabling:
- LLM Integration - Convert documents to Markdown for use with Large Language Models
- Text Analysis - Prepare documents for automated text analysis and NLP pipelines
- Knowledge Extraction - Preserve document structure while extracting content
- Batch Processing - Handle multiple documents efficiently
- Language: Python 3.10+
- Web Framework: Flask with Werkzeug
- Document Processing: MarkItDown with optional PDF/Office support
- PDF Libraries: pypdf, pdfplumber
This project was created to provide an accessible web interface for the MarkItDown library, making document conversion available to users who prefer a graphical interface over command-line tools.
- app.py - Flask web application serving the conversion interface
- convert_catalogue.py - Batch conversion utility for processing multiple files
- packages/markitdown/ - Core MarkItDown library for format support
- packages/markitdown-ocr/ - OCR support for scanned documents (optional)
- packages/markitdown-mcp/ - Model Context Protocol integration
- static/ - Frontend assets (CSS, JavaScript)
- templates/ - HTML templates for the web interface
The project required several dependencies that weren't initially declared:
- flask - Web application framework
- werkzeug - WSGI toolkit for Flask
- pypdf - PDF processing library used by app.py
- pdfplumber - PDF text extraction and table processing
- markitdown[pdf,pptx,docx,xlsx,xls,outlook] - Core conversion library with format-specific support
These have been documented in requirements.txt for reproducible installation.
Potential improvements could include:
- Docker containerization for easy deployment
- Batch upload and processing
- API endpoints for programmatic access
- Output format options (JSON, YAML, etc.)
- Document preview functionality
- File format detection and validation
- Custom conversion templates
This is an open project. Contributions, bug reports, and feature requests are welcome.
See LICENSE in the markitdown directory for details.