What Security Teams Should Require From an MCP Gateway

MCP gateways are becoming crucial in enterprise AI deployments, yet they often lack necessary security controls, leading to significant vulnerabilities. The primary risks include inadequate tool permissions, insufficient user scoping, unannounced vendor-side changes, fragmented policies across AI clients, and exposure of sensitive data. MCP gateways serve as policy enforcement layers, controlling access and protecting data between AI agents and MCP servers. Effective MCP security requires per-tool policy enforcement, identity-driven access control, change management workflows, and real-time data protection, with policies ideally being code-based for better management and auditability. Security teams must ensure these controls are in place to mitigate the inherent risks associated with MCP deployments, emphasizing the need for a centralized control plane and comprehensive policy lifecycle management.