An AI agent becomes useful when it can work with tools and enterprise data. Every connection, however, is also a new permission boundary.
Our Central MCP (CMCP) concept explores a governed way to expose tools to agents: clear identities, narrowly scoped capabilities, policies and traceable calls.
Instead of granting an agent broad access to production systems, a central layer can mediate what it may discover and invoke. Sensitive actions should require additional checks or human approval.
CMCP is an architectural direction we are exploring, not a claim that a finished gateway is already available.
OUR PRINCIPLE
Explicit decisions. Governed execution. Verifiable outcomes.