This paper introduces urb.io, an interactive optimization framework for early-stage urban planning. It allows urban planners to generate and explore many alternative urban configurations, while focusing their attention on the most promising ones. First, addressing the need for integrated urban modeling approaches, a Mixed Integer Linear Programing (MILP) optimization model representing both urban and energy system components was developed. Second, an interface based on parallel coordinates and georeferenced maps is proposed to effectively communicate the optimization results to decision makers, revealing tradeoffs and synergies between competing objectives. Interaction with the parallel coordinates charts further allows planners to steer consec- utive optimization runs based on their preferences and experience. The framework is applied to an urban development project in Switzerland to demonstrate its usability and relevance.