CodeDox - AI-Powered Documentation Search & Code Extraction
Transform any documentation site into a searchable code database - CodeDox crawls documentation websites, intelligently extracts code snippets with context, and provides lightning-fast search via PostgreSQL full-text search and MCP (Model Context Protocol) integration for AI assistants.
📚 Documentation
For full documentation, installation guides, API reference, and more, visit:
Quick Start
Docker Setup (Recommended)
# Clone the repository
git clone https://github.com/chriswritescode-dev/codedox.git
cd codedox
# Configure environment
cp .env.example .env
# Edit .env to add your CODE_LLM_API_KEY (optional for AI-enhanced extraction)
# Run the automated setup
./docker-setup.sh
# Access the web UI at http://localhost:5173
Manual Installation
See the full installation guide for detailed instructions.
Key Features
- Intelligent Web Crawling: Depth-controlled crawling with URL pattern filtering and domain restrictions
- Smart Code Extraction: Dual-mode extraction (AI-enhanced snippet descriptions or standalone)
- Lightning-Fast Search: PostgreSQL full-text search with fuzzy matching
- GitHub Repository Processing: Clone and extract documentation from GitHub repositories with full path support (e.g.,
/tree/main/docs
)
- MCP Integration: Native Model Context Protocol support for AI assistants
- Modern Web Dashboard: React + TypeScript UI for visual management
- Version Support: Track multiple versions of documentation
- Real-time Monitoring: Live crawl progress and health monitoring
- Upload Support: Upload documentation directly (Markdown, HTML, TXT) or from GitHub repositories
Demo - MCP Integration Example - OpenCode TUI
Screenshots
Dashboard
Markdown Search with Highlighting
Source Detail View
Documentation
Contributing
See our Contributing Guide for details on how to contribute to CodeDox.
Author
Chris Scott - chriswritescode.dev
License
This project is licensed under the MIT License - see the LICENSE file for details.