Material choices fixed early in design determine much of a building’s embodied carbon and how much of its material can later be recovered, but the data needed to weigh the two are usually held in separate tools. To bring them together, a deterministic process was implemented that reads Industry Foundation Classes (IFC) data, enumerates whole-building material scenarios, filters them for Pareto dominance, answers controlled semantic queries, and packages the results as prompt text for optional downstream interpretation. One buildingSMART reference IFC model yielded seven valid components, and 150 wall-floor-roof material configurations were evaluated on that basis. Twelve configurations were non-dominated: six low-carbon-oriented configurations, in which timber systems predominate, and six circularity-oriented configurations built on aluminium-roof systems. The same candidates were returned under all five Building Circularity Score (BCS) weighting schemes (12/12 overlap with the equal-weight baseline), and the classification of 0 balanced, 6 low-carbon-oriented, and 6 circularity-oriented scenarios held across nine threshold combinations. In a scenario-based Monte Carlo check, every one of the 12 baseline candidates stayed non-dominated in at least 83.2% of 1000 sampled runs under the stated assumptions. The full 150-configuration case took approximately 0.79 s, of which pairwise Pareto filtering accounted for approximately 0.023 s. Within this single test case, IFC-derived quantities were sufficient for a reproducible environmental ranking, and the outputs are candidate scenarios for prototype-stage decision support, not complete design prescriptions. External validation, additional IFC models, engineering feasibility checks, and deployment beyond the prototype are left to future work.