OpenSCAD MCP Server

# Implementation Plan: OpenSCAD-MCP-Server with AI-Driven 3D Modeling ## 1. Project Structure Updates ### 1.1 New Modules ``` src/ ├── ai/ │ ├── venice_api.py # Venice.ai API client │ └── sam_segmentation.py # SAM2 integration ├── models/ │ └── threestudio_generator.py # threestudio integration └── workflow/ └── image_to_model_pipeline.py # Workflow orchestration ``` ### 1.2 Dependencies Add to requirements.txt: ``` # Image Generation - Venice.ai API # (using existing requests and python-dotenv) # Object Segmentation - SAM2 torch>=2.0.0 torchvision>=0.15.0 opencv-python>=4.7.0 segment-anything>=1.0 # 3D Model Creation - threestudio ninja>=1.11.0 pytorch3d>=0.7.4 trimesh>=3.21.0 ``` ## 2. Component Implementation ### 2.1 Venice.ai API Integration - Create `VeniceImageGenerator` class in `venice_api.py` - Implement authentication with API key - Add image generation with Flux model - Support image downloading and storage ### 2.2 SAM2 Integration - Create `SAMSegmenter` class in `sam_segmentation.py` - Implement model loading with PyTorch - Add object segmentation from images - Support mask generation and visualization ### 2.3 threestudio Integration - Create `ThreeStudioGenerator` class in `threestudio_generator.py` - Implement 3D model generation from masked images - Support model export in formats compatible with OpenSCAD - Add preview image generation ### 2.4 OpenSCAD Integration - Extend `OpenSCADWrapper` with methods to: - Import 3D models from threestudio - Generate parametric modifications - Create multi-angle previews - Export in various formats ### 2.5 Workflow Orchestration - Create `ImageToModelPipeline` class to coordinate the workflow: 1. Generate image with Venice.ai API 2. Segment object with SAM2 3. Create 3D model with threestudio 4. Import into OpenSCAD for parametric editing ## 3. MCP Tool Integration Add new MCP tools to main.py: - `generate_image_from_text`: Generate images using Venice.ai - `segment_object_from_image`: Segment objects using SAM2 - `generate_3d_model_from_image`: Create 3D models using threestudio - `generate_model_from_text`: End-to-end pipeline from text to 3D model ## 4. Hardware Requirements - SAM2: NVIDIA GPU with 6GB+ VRAM - threestudio: NVIDIA GPU with 6GB+ VRAM - Consider implementing fallback options for environments with limited GPU resources ## 5. Implementation Phases ### Phase 1: Basic Integration - Implement Venice.ai API client - Set up SAM2 with basic segmentation - Create threestudio wrapper with minimal functionality - Extend OpenSCAD wrapper for model import ### Phase 2: Workflow Orchestration - Implement the full pipeline - Add MCP tools for each component - Create end-to-end workflow tool ### Phase 3: Optimization and Refinement - Optimize for performance - Add error handling and recovery - Implement corrective cycle for mesh modification - Add user interface improvements