This letter introduces a dedicated processor architecture, called MEGACORE, which leverages vector technology to enhance tracking performance in visual simultaneous localization and mapping (VSLAM) systems. By harnessing the inherent parallelism of vector processing and incorporating a floating point unit (FPU), MEGACORE achieves significant acceleration in the tracking task of VSLAM. Through careful optimizations, we achieved notable improvements compared to the baseline design. Our optimizations resulted in a 14.9% reduction in the area parameter and a 4.4% reduction in power consumption. Furthermore, by conducting application benchmarks, we determined that the average speedup ratio across all stages of the tracking process is 3.25. These findings highlight the effectiveness of MEGACORE in improving the efficiency and performance of VSLAM systems, making it a promising solution for real-world implementations in embedded systems.