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OpenSCAD MCP Server

by jhacksman
main.py.md2.57 kB
<metadata> author: devin-ai-integration timestamp: 2025-03-21T01:30:00Z version: 1.0.0 related-files: [/src/ai/ai_service.py, /src/models/code_generator.py, /src/nlp/parameter_extractor.py] prompt: "Build an MCP server for OpenSCAD" </metadata> <exploration> The main application was designed to implement a Model Context Protocol (MCP) server for OpenSCAD integration. Several approaches were considered: 1. Using a standalone server with direct OpenSCAD CLI calls 2. Implementing a web service with REST API 3. Creating an MCP-compliant server with FastAPI The MCP-compliant FastAPI approach was selected for its alignment with the project requirements and modern API design. </exploration> <mental-model> The main application operates on a "tool-based MCP service" paradigm, where each capability is exposed as an MCP tool that can be called by AI assistants. This mental model aligns with the MCP specification and provides a clean separation of concerns. </mental-model> <pattern-recognition> The implementation uses the Facade pattern to provide a simple interface to the complex subsystems (parameter extraction, code generation, OpenSCAD wrapper, etc.). This pattern simplifies the client interface and decouples the subsystems from clients. </pattern-recognition> <trade-off> Options considered: 1. Monolithic application with tightly coupled components 2. Microservices architecture with separate services 3. Modular monolith with clear component boundaries The modular monolith approach was chosen because: - Simpler deployment and operation - Lower latency for inter-component communication - Easier to develop and debug - Still maintains good separation of concerns </trade-off> <domain-knowledge> The implementation required understanding of: - Model Context Protocol (MCP) specification - FastAPI framework - OpenSCAD command-line interface - 3D modeling and printing workflows </domain-knowledge> <technical-debt> The current implementation has some limitations: - In-memory storage of models (not persistent) - Basic error handling - Limited printer discovery capabilities Future improvements planned: - Persistent storage for models - Enhanced error handling and reporting - More robust printer discovery and management </technical-debt> <knowledge-refs> [OpenSCAD Basics](/rtfmd/knowledge/openscad/openscad-basics.md) - Last updated 2025-03-21 [AI-Driven Code Generation](/rtfmd/decisions/ai-driven-code-generation.md) - Last updated 2025-03-21 </knowledge-refs>

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