Aiming to address the challenges posed by multiple decision elements and a vast decision space in multi-spacecraft mission planning, a multi-spacecraft mission allocation planning algorithm based on potential games is proposed to enhance the efficiency of multi-spacecraft distributed mission planning. Additionally, an adaptive particle swarm algorithm is introduced for further improvement and optimization. First, a comprehensive mission planning model is developed based on mission matching degree, mission time constraints, and energy consumption constraints. In mapping the mission planning model to the Potential Game model, a distributed mission allocation algorithm is proposed. In addition, the Adaptive Particle Swarm Algorithm is introduced into the mission allocation algorithm to solve the problem of finding the global optimal solution. Finally, experimental examples show the feasibility of the model as well as algorithm selection is correct.