The US Army envisions heterogeneous teams of advanced machines and humans that will collaborate together to achieve a common mission goal. It is essential for commanders to quickly and effectively respond to dynamic mission environments with agile re-tasking and computerized aids for plan definition/redefinition, and to perform some tasks with bounded autonomy. Workload constraints limit an individual's ability to concurrently control many platforms, so some mission segments many need to be autonomous or to be quickly selected via a tactics playbook. Denied environments also dictate the need for machine participants in some mission segments to be autonomous (or semi-autonomous). A Multi-Agent System (MAS) provides a natural paradigm for describing a system of agents that work together in such environments. An agent can be a human or machine, but is generally a machine. Creating MAS systems and requirements has proved to be a formidable task due to mission complexities, the necessity to deal with unforeseen circumstances, and the general difficulty of defining autonomous behaviors. We define a process called Multi-Agent Systems Collaborative Teaming (MASCOT) Definition Process that starts with a Subject Matter Experts (SME), produces a set of agent specifications, and derives system requirements in sufficient detail to define a MAS that can be modeled in a test-bed, used for facilitation of a safety analysis, and produced into an actual system. The MASCOT process also enables concurrent development of an effects based ontology. We demonstrate the MASCOT process on an example case study to show the efficacy of our process.