In this paper, we consider an automated approach to the optimal multi-objective design of parallel robots. Optimization is performed according to two key characteristics: the workspace area and the global dexterity index (GDI). The workspace is a set of points that the robot can serve. The value of the GDI correlates with the quality of this service. Both objectives should be maximized. However, there is a tradeoff between these goals and they can’t achieve maximums at the same point. Therefore, the solution for this problem is a set of Pareto-optimal points (that can’t be optimized in any criteria without worsening the other). The paper describes the methodology and the software for computing the workspace area, the GDI, and approximating the Pareto set for the multi-objective optimization problem under consideration. The user interface enables efficient visualization of the robot workspace and dependencies of the robot’s key characteristics on various design parameters.