Significance Magnetic soft continuum robots (MSCRs) capable of magnetic field–controllable steering offer great promise for the endovascular treatment of cardiovascular diseases. However, existing MSCRs are often limited to small workspaces because of the lack of efficient design and optimization tools. In this work, we introduce an evolutionary design strategy by integrating theoretical modeling and the genetic algorithm. Enabled by this strategy, the proposed MSCR achieves an optimal workspace much larger than those of the state-of-the-art MSCRs. The proposed design strategy also offers a potent tool for efficient design and optimization of future magnetic soft robots and actuators.