Establishing the fundamental understanding of the nature of materials via computational simulation approaches requires knowledge from various fields, including physics, materials science, chemistry, mechanical engineering, mathematics, and computer science. Accurate modeling of the characteristics of a particular system usually involves multiple scales and therefore requires the combination of methods from various fields into custom-tailored simulation workflows. In many material modeling groups worldwide, the approach to design the simulation protocols requires extensive expertise in scripting, command-line execution, and knowledge on all methods and tools involved for data preparation, data transfer between modules, module execution, and analysis. Therefore multiscale simulations involving state-of-the-art methods suffer from limited scalability, reproducibility, and flexibility. Here, we present the framework SimStack that enables rapid prototyping of simulation workflows involving modules from various sources. In this platform, multiscale and multimodule workflows for execution on remote computational resources are crafted via drag\&drop, minimizing required expertise and effort for workflow setup, hiding the complexity of high-performance computations on remote resources, and maximizing reproducibility. SimStack thereby allows users from academia and industry to combine competitive edge models into custom-tailored, scalable simulation solutions.