Generative Design Proposals via LLM-BIM IntegrationKhan, Sangeen (Avtor) Turk, Žiga (Mentor) master thesiscivil engineeringmodel context protocolnatural language promptsbuilding information modelingAI-BIM integrationbidirectional communicationconversational interfacesLarge Language Models (LLMs) have unique advantages and potential in Building Information Modeling (BIM) environments. Their methodology supports natural language interaction with complex design software, offering efficient communication between AI systems and BIM-based platforms. However, for structural and architectural modeling workflows, the integration capacity of existing AIBIM approaches presents some limitations that must be resolved with best possible solutions. These challenges include unidirectional communication patterns and complex programming requirements that hinder implementing conversational AI workflows in BIM design offices. This study focuses to analyze the process of enabling bidirectional communication between LLMs and BIM software while developing a unique workflow for implementation within design tools, AI platforms, and project teams. Two case studies have been developed to test practical interoperability workflows: BIMCP for Autodesk Revit integration and Kolektor-BONCP for IFC manipulation through Blender's Bonsai addon. This is to identify and resolve the limitations involved in natural language command processing and data flow between AI assistants and the BIM software. The communication processes are bidirectional, using the Model Context Protocol (MCP) framework and socket-based connections for real-time interaction. AI-BIM integration and conversational design workflows are relatively underutilized. This is mainly due to interoperability problems and accessibility barriers. Despite the identified limitations and technical challenges, the study outcomes within the case study development illustrate how the workflow has excellent advantages in developing AI-assisted BIM projects and its implementation in construction industry design offices. Real-world validation at Kolektor Koling demonstrates measurable productivity improvements, transforming multi-hour manual processes into minute-long conversational queries.[S. Khan]20252025-08-05 08:45:04Magistrsko delo/naloga171102UDK: 004.42:69(043.2)VisID: 172771COBISS_ID: 245263107sl