Multi-Agent-CAD
by Pan-Chera
Decoupled multi-agent pipeline to turn text into CAD (STEP) files
Overview
Coordinates multiple specialized agents to convert text prompts into CAD models. Uses a decoupled pipeline where agents handle interpretation, constrained geometry synthesis, and file export under test-time compute limits. Stands out by combining modular agent roles with CAD toolchains (Build123d/OpenCASCADE) to produce STEP outputs from natural language. This approach aligns with the Role-Based Agent Pattern for structuring modular agent roles.
Why It Matters
Best For
Researchers and engineers building and iterating on text-to-CAD agent pipelines who need modular roles and constrained test-time compute. The toolchain can benefit from standardized coordination and context-sharing, such as the Model Context Protocol (MCP). For robust agent collaboration strategies, practitioners may also explore the Supervisor Pattern.
Use Cases
- Convert natural language design briefs into parametrized STEP files via specialist agents
- Split CAD generation into interpreters, geometry creators, and exporters to isolate failure modes
- Run constrained test-time compute experiments to compare agent strategies for reliable CAD outputs