Model Predictive Control (MPC) is a promising control strategy for matrix converters in grid-interactive applications. MPC optimizes a cost function over a finite time horizon, considering system constraints like voltage and current limits, grid codes, and power factor requirements. This enables effective grid synchronization, power quality regulation, and efficient power conversion. Advancements in MPC include predictive modelling techniques, adaptive algorithms, optimization algorithm integration, hybrid control strategies, and multi-objective optimization formulations. Benefits include fast response to changes in grid conditions, robustness in handling uncertainties, and extended time-horizon optimization. This study provides insights into MPC techniques and highlights the potential for further research.