Large language models (LLMs) can assist engineering workflows, but their direct application in structural analysis is fundamentally limited by numerical inconsistencies, prompt sensitivity, and context degradation. To address these bottlenecks, a verification-and-refinement driven multi-agent framework is proposed. The five-stage pipeline uses an explicit verify–correct loop to improve engineering consistency and incorporates a Model Context Protocol (MCP) hybrid path. This MCP architecture routes highly complex numerical structural calculations to a deterministic external solver under predefined trigger conditions. The methodology was evaluated on two cases: (A) a benchmark frame collapse-analysis problem resolved purely within the LLM verify–correct loop, and (B) an eight-story steel moment-resisting frame where trigger-based routing invoked MATLAB for high-DOF second-order analysis. Across the evaluations, the iterative pipeline increased verification pass rates, with the largest gain occurring during the first verify–correct iteration. Staged prompts and structured JSON/Markdown handoffs also limited context inflation. In Case B, the MCP-delegated numerical solve returned reports that satisfied drift and equilibrium requirements. These results suggest that an iterative verification pipeline combined with policy-guided external-solver delegation can improve reliability in complex structural engineering problems.
Seokjae Heo (Mon,) studied this question.