Keeping you up to date on AI and Model Context Protocol (MCP)

🏗️ ClaudeHopper - AI-Powered Construction Document Assistant

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 for local AI models
- Required models: nomic-embed-text, phi4, clip
Claude Desktop App
For image extraction: Poppler Utils (pdfimages command)

One-Click Setup

Download ClaudeHopper
Run the setup script:

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:

./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:

Document Analysis: PDF documents are analyzed for structure and content type
Metadata Extraction: AI-assisted extraction of project information, drawing types, disciplines
Content Chunking: Intelligent splitting of documents to maintain context
Image Extraction: Identification and extraction of drawing images from PDFs
Vector Embedding: Creation of semantic representations for text and images
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:

## 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:

## 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 file.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.