As computational paradigms evolve, applications such as attention-based models, wireless telecommunications, and computer vision impose increasingly challenging requirements on computer architectures: significant memory footprints and computing resources are demanded while maintaining flexibility and programmability at a low power budget. Thanks to their advantageous trade-offs, shared-L1-memory clusters have become a common building block of massively parallel computing architectures tackling these issues. MemPool is an open-source, RISC-V-based manycore cluster scaling up to 1024 processing elements (PEs). MemPool offers a scalable, extensible, and programmable solution to the challenges of shared-L1 clusters, establishing itself as an open-source research platform for architectural variants covering a wide trade-off space between versatility and performance. As a demonstration, this paper compares the three main MemPool flavors, Baseline MemPool, Systolic MemPool, and Vectorial MemPool, detailing their architecture, targets, and achieved trade-offs.