Port of Context launches a token-efficient MCP context layer for regulated firms

Port of Context launched a self-hostable MCP context layer aimed at regulated industries, aggregating existing MCP servers behind one endpoint and exposing their tools to agents as code. Its code mode cites an Agentic AI Foundation case study in which each run fell from 93.6k to 31.8k input tokens at half the cost, and the platform runs on Claude, GPT, Gemini or open-weight models in a customer's cloud, on-prem or air-gapped network, with the core MIT-licensed and every run traced under its open AVP observability spec.