Enterprises need four governance layers, not one tool, to secure AI agents accessing APIs.
MCP servers now handle production data at scale, but most skip basic security controls.
Securing MCP requires governance infrastructure enterprises haven't yet built.
Platform teams need patterns to govern MCP servers before production locks in consequences.
Enterprises can't find their own MCP servers, creating silent security risks.
A central gateway enforces authentication and policy across AI agents and tools.
MCP and API gateways solve different problems; confusing them leaves security gaps.
Enterprises need separate governance layers because the protocol only secures the wire.
Most enterprises run AI agents without centralized controls to manage who accesses what.
Four structural problems block enterprises from safely governing AI agent permissions at scale.
Workload identity tokens and least-privilege scoping close the governance gap agents create.
AI agents outpace security controls built for human employees.
