# MedVision MCP
Medical Vision AI Tools via Model Context Protocol (MCP)
## Overview
MedVision MCP provides AI-powered medical image analysis tools accessible through the [Model Context Protocol](https://modelcontextprotocol.io/). It enables LLM agents (like Claude, GitHub Copilot) to analyze chest X-rays using Visual RAG (RAD-DINO + FAISS + DenseNet).
## Features
- ✅ **DenseNet Classification**: 18 pathology detection (Lung Opacity, Pneumonia, etc.)
- ✅ **RAD-DINO Embeddings**: 768-dim visual embeddings for similarity search
- ✅ **FAISS Index**: Fast similarity search for similar historical cases
- ✅ **DICOM Support**: Native DICOM file reading
- ✅ **Gradio Canvas**: Interactive ROI drawing/annotation interface
- ✅ **ROI Analysis**: Analyze specific regions drawn on X-rays
- 🔜 **Medical SAM**: SAM-based region segmentation
## Quick Start
```bash
# Clone
git clone https://github.com/u9401066/medvision-mcp.git
cd medvision-mcp
# Install with uv
uv sync
# Test classification
uv run python -c "
import asyncio
from src.medvision_mcp.server import classify_xray
async def main():
result = await classify_xray('path/to/xray.dcm')
print(result)
asyncio.run(main())
"
```
## MCP Tools
| Tool | Description |
|------|-------------|
| `analyze_xray` | Full Visual RAG analysis (classification + similarity) |
| `classify_xray` | Quick DenseNet-121 classification (18 pathologies) |
| `search_similar_cases` | RAG similarity search |
| `build_rag_index` | Build FAISS index from image directory |
| `load_rag_index` | Load pre-built index |
| `get_engine_status` | Check model loading status |
## Gradio UI
Launch the interactive web UI:
```bash
# Start Gradio server
uv run python -m src.medvision_mcp.ui.app
# Open http://localhost:7860
```
**UI Tabs:**
| Tab | Description |
|-----|-------------|
| 📊 Analysis | Full image analysis (classification + RAG) |
| ⚡ Quick Classify | Fast 18-pathology classification |
| 🎨 Canvas ROI | **Draw ROIs** and analyze specific regions |
| 🔧 Build Index | Create FAISS index from images |
| 📂 Load Index | Load pre-built index |
| ℹ️ Status | Check model loading status |
## Claude Desktop Configuration
Add to `~/.config/claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"medvision": {
"command": "uv",
"args": ["run", "--directory", "/path/to/medvision-mcp", "python", "-m", "src.medvision_mcp.server"]
}
}
}
```
## Architecture
```
┌─────────────────────────────────────────────────────────┐
│ MCP Client (Claude, Copilot) │
└─────────────────────────┬───────────────────────────────┘
│ stdio
┌─────────────────────────▼───────────────────────────────┐
│ MedVision MCP Server │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │
│ │ classify │ │ search │ │ analyze │ │
│ │ _xray │ │ _similar │ │ _xray │ │
│ └─────────────┘ └─────────────┘ └─────────────────┘ │
│ │ │
│ ┌───────────────────────▼────────────────────────────┐ │
│ │ Visual RAG Engine │ │
│ │ RAD-DINO │ FAISS │ DenseNet-121 │ │
│ └────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────┘
```
## Development
```bash
# Install dev dependencies
uv sync --dev
# Run tests
uv run pytest
# Check types
uv run pyright
```
## License
MIT
