OpenSCAD MCP Server

<metadata> author: devin-ai-integration timestamp: 2025-03-21T01:30:00Z version: 1.0.0 related-files: [/src/models/code_generator.py] prompt: "Implement AI-driven code generator for OpenSCAD" </metadata> <exploration> The AI service component was designed to provide natural language processing capabilities for generating OpenSCAD code from user descriptions. Initial approaches considered: 1. Using a template-based approach with predefined patterns 2. Implementing a full NLP pipeline with custom entity extraction 3. Creating a hybrid approach that combines pattern matching with contextual understanding The hybrid approach was selected as it provides flexibility while maintaining performance. </exploration> <mental-model> The AI service operates on the concept of "component identification" - breaking down natural language descriptions into geometric primitives, operations, features, and modifiers. This mental model aligns with how OpenSCAD itself works, where complex models are built from primitive shapes and CSG operations. </mental-model> <pattern-recognition> The implementation uses the Strategy pattern for different parsing strategies and the Factory pattern for code generation. These patterns allow for extensibility as new shape types or operations are added. </pattern-recognition> <trade-off> Options considered: 1. Full machine learning approach with embeddings and neural networks 2. Rule-based pattern matching with regular expressions 3. Hybrid approach with pattern matching and contextual rules The hybrid approach was chosen because: - Lower computational requirements than full ML - More flexible than pure rule-based systems - Easier to debug and maintain - Can be extended with more sophisticated ML in the future </trade-off> <domain-knowledge> The implementation required understanding of: - OpenSCAD's modeling paradigm (CSG operations) - Common 3D modeling terminology - Natural language processing techniques - Regular expression pattern matching </domain-knowledge> <knowledge-refs> [OpenSCAD Basics](/rtfmd/knowledge/openscad/openscad-basics.md) - Last updated 2025-03-21 [Natural Language Processing](/rtfmd/knowledge/ai/natural-language-processing.md) - Last updated 2025-03-21 </knowledge-refs>