Direct air capture (DAC) is regarded as a key option for long-term carbon dioxide removal (CDR) due to its scalability, siting flexibility, and compatibility with permanent geological storage. However, large-scale development of DAC remains challenging, with further cost reductions being critical. Recent research work indicates that at a cumulative capacity of 1 Gt CO2/y, DACCS costs are projected to $226-835/tCO2, underscoring the importance of continued innovation [1]. Recent studies indicate that system-level performance and further cost reduction potential is often limited by water management, contactor productivity, auxiliary energy demand, and balance-of-plant design, highlighting the need to move beyond sorbent-centered optimization toward integrated, multi-scale system analysis[2]. Most of DAC technologies discussed to date rely on aqueous scrubbing or solid sorbents regenerated through temperature-vacuum swing adsorption (TVSA), both of which require substantial thermal energy inputs[3]. In contract, moisture swing adsorption (MSA) has merged as a promising alternative that enables regeneration through humidity control, relying primarily on electricity and offering modular systems design. Beyond carbon removal, MSA process inherently interact with atmospheric water, creating opportunities for coupled water management and hybrid system designs. These characteristics suggest that MSA and related hybrid DAC concepts may offer greater flexibility across scales and locations, as well as enhanced resilience through integration with low-grade heat sources, such as data centers, under uncertain policy and infrastructure conditions. This work presents JuDCB-DAC, an open-source modeling framework developed in Julia for prospective life cycle and techno-economic assessment of hybrid DAC systems. The framework integrates isothermal and breakthrough-curve modeling, with process-level and system-level optimization. Hybrid configurations combining moisture swing adsorption (MSA) and atmospheric water extraction (AWE) are explicitly considered, enabling the analysis of coupled temperature–humidity effects, regeneration strategies, and operational flexibility under varying climatic conditions. JuDCB-DAC embeds regionalized and prospective life cycle assessment, accounting for regional electricity mixes, water availability, ambient temperature and humidity, and CO₂ storage distances. A scenario-based optimization approach is used to explore trade-offs among energy demand, water use, costs, and life cycle carbon removal efficiency across locations and deployment scales. By providing a transparent, modular, and extensible open-source platform, this work enables consistent comparison of hybrid DAC configurations, supports location-specific CDR strategy design.