We provide an implementation of the Multi-agent Transformer algorithm in JAX. MAT casts cooperative multi-agent reinforcement learning as a sequence modelling problem where agent observations and actions are treated as a sequence. At each timestep the observations of all agents are encoded and then these encoded observations are used for auto-regressive action selection.