Contextual Anomaly Detection in Quantum-Resistant MCP Transport Layers

The post analyzes the hidden environmental and operational footprint of AI systems, detailing high electricity and cooling needs, substantial water use for data center cooling, rapid hardware turnover and e‑waste, and ongoing inference energy costs; it also discusses governance gaps that cause "ghost" agents and offers mitigation strategies like serverless architectures, model quantization, caching, and region-based routing to reduce carbon and resource impacts.