Urban Digital Twins (UDTs) are increasingly adopted to support evidence-based urban planning, municipal management, and municipal decision-making. However, many municipalities still lack the integrated geospatial infrastructure required to transform conventional mapping products into operational digital twin environments. This study proposes a Municipal Digital Twin Readiness Framework that systematically transforms UAV-derived geospatial data into a multi-representation three-dimensional (3D) geospatial infrastructure supporting future digital twin implementation. The framework consists of four sequential stages: (1) geospatial data acquisition and preprocessing using UAV photogrammetry, (2) automated generation of multi-representation 3D urban models through AI-assisted semantic extraction and urban object reconstruction, (3) development of an interoperable spatial data infrastructure based on open-source geospatial technologies, and (4) deployment of an operational web-based 3D geoportal through the UrbanScope platform. The framework was implemented in Cimahi City, Indonesia, demonstrating five progressive Municipal Digital Twin Readiness levels. The proposed approach supports complementary urban representations, including semantic city models, semantic meshes, and neural rendering models, according to different analytical and visualization requirements. The proposed framework provides municipalities with a scalable and replicable pathway for establishing interoperable multi-representation geospatial infrastructures that underpin future Urban Digital Twin ecosystems.