Model Compression Toolkit (MCT) provides advanced post-training quantization (PTQ) and quantization-aware training (QAT) capabilities for neural networks. It supports both PyTorch and TensorFlow frameworks, enabling researchers and engineers to compress models for edge deployment while maintaining accuracy. The toolkit targets efficient inference on hardware-constrained environments.