LLM Proxies vs. MCP Gateways: What's the Difference?
Security Boulevard, Tuesday, April 28th, 2026
LLM proxies and MCP gateways are distinct AI infrastructure components that serve different purposes in enterprise AI architectures.
LLM proxies are lightweight intermediaries that manage how requests are routed to model providers like OpenAI and Anthropic, handling token tracking, cost monitoring, and API key abstraction. MCP gateways, by contrast, focus on governing how AI agents interact with external tools, databases, and systems through the Model Context Protocol, providing access control and workflow orchestration.
While both serve as intermediaries that reduce developer complexity, they address fundamentally different challenges: proxies manage model traffic while gateways control agent actions and multi-step task execution. As organizations scale AI adoption beyond simple use cases to build agent-driven systems, the distinction becomes critical for managing security risks and maintaining visibility across AI operations.