ClaudeHopper

# 🏗️ ClaudeHopper - AI-Powered Construction Document Assistant [](https://nodejs.org/en/) [](https://opensource.org/licenses/MIT) ClaudeHopper is a specialized Model Context Protocol (MCP) server that enables Claude and other LLMs to interact directly with construction documents, drawings, and specifications through advanced RAG (Retrieval-Augmented Generation) and hybrid search. Ask questions about your construction drawings, locate specific details, and analyze technical specifications with ease. ## ✨ Features - 🔍 Vector-based search for construction document retrieval optimized for CAD drawings, plans, and specs - 🖼️ Visual search to find similar drawings based on textual descriptions - 🏢 Specialized metadata extraction for construction industry document formats - 📊 Efficient token usage through intelligent document chunking and categorization - 🔒 Security through local document storage and processing - 📈 Support for various drawing types and construction disciplines (Structural, Civil, Architectural, etc.) ## 🚀 Quick Start ### Prerequisites - Node.js 18+ - [Ollama](https://ollama.com/) for local AI models - Required models: `nomic-embed-text`, `phi4`, `clip` - Claude Desktop App - For image extraction: [Poppler Utils](https://poppler.freedesktop.org/) (`pdfimages` command) ### One-Click Setup 1. Download ClaudeHopper 2. Run the setup script: ```bash cd ~/Desktop/claudehopper chmod +x run_now_preserve.sh ./run_now_preserve.sh ``` This will: - Create the necessary directory structure - Install required AI models - Process your construction documents - Configure the Claude Desktop App to use ClaudeHopper ### Adding Documents Place your construction documents in these folders: - Drawings: `~/Desktop/PDFdrawings-MCP/InputDocs/Drawings/` - Specifications: `~/Desktop/PDFdrawings-MCP/InputDocs/TextDocs/` After adding documents, run: ```bash ./process_pdfdrawings.sh ``` ## 🏗️ Using ClaudeHopper with Claude Try these example questions in the Claude Desktop App: ``` "What architectural drawings do we have for the project?" "Show me the structural details for the foundation system" "Find drawings that show a concrete foundation with dimensions" "Search for lift station layout drawings" "What are the specifications for interior paint?" "Find all sections discussing fire protection systems" ``` ## 🛠️ Technical Architecture ClaudeHopper uses a multi-stage pipeline for processing construction documents: 1. **Document Analysis**: PDF documents are analyzed for structure and content type 2. **Metadata Extraction**: AI-assisted extraction of project information, drawing types, disciplines 3. **Content Chunking**: Intelligent splitting of documents to maintain context 4. **Image Extraction**: Identification and extraction of drawing images from PDFs 5. **Vector Embedding**: Creation of semantic representations for text and images 6. **Database Storage**: Local LanceDB storage for vector search capabilities ## 👀 Testing the Image Search To test the image search functionality, you can use the provided test script: ```bash # Make the test script executable chmod +x test_image_search.sh # Run the test script ./test_image_search.sh ``` This will: - Build the application - Check for required dependencies (like `pdfimages`) - Seed the database with images from your drawings directory - Run a series of test queries against the image search You can also run individual test commands: ```bash # Run the test with the default database location npm run test:image:verbose # Run the test with a specific database location node tools/test_image_search.js /path/to/your/database ``` ## 📝 Available Search Tools ClaudeHopper provides several specialized search capabilities: - `catalog_search`: Find documents by project, discipline, drawing type, etc. - `chunks_search`: Locate specific content within documents - `all_chunks_search`: Search across the entire document collection - `image_search`: Find drawings based on visual similarity to textual descriptions Examples of using the image search feature can be found in the [image_search_examples.md](examples/image_search_examples.md) file. ## 📜 License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.