Multi-Agent Visual Tracking implements a distributed tracking system composed of intelligent agents that communicate to improve accuracy and robustness in video object tracking. Agents run convolutional neural networks for detection, share observations to handle occlusions, and adjust tracking parameters through reinforcement learning. Compatible with popular video datasets, it supports both training and real-time inference. Users can easily integrate it into existing pipelines and extend agent behaviors for custom applications.