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Our goal is to apply mobile agent technology to provide a better scheduling for MPI applications executing in a cluster configuration. This approach could represent in a distributed cluster environment an enhancement on the load balancing of the parallel processes. MPI in a cluster of heterogeneous machines could lead parallel programmers to obtain frustrated results, mainly because of the lack of an even distribution of the workload in the cluster. As a result, before submitting a MPI application to a cluster, we use our JOTA mobile agent approach to acquire a more precise information of machine's workload. Therefore, with a more precise knowledge of the load and characteristics in each machine, we are ready to gather lightweight workstations to form a cluster. Our empirical results indicate that it is possible to spend less elapsed time when considering the execution of a parallel application using the agent approach in comparison to an ordinary MPI environment.