As enterprise adoption of generative AI accelerates, so does the number of new components showing up in architecture diagrams. Among the common are LLM proxies and MCP gateways. They are often grouped together because they both sit between applications and AI systems, and both introduce a level of abstraction that is intended to simplify development The post LLM Proxies vs. MCP Gateways: What’s the Difference? appeared first on Cequence Security.

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LLM proxies and MCP gateways are both intermediaries in AI architectures but solve different problems. LLM proxies handle model traffic routing, token tracking, failover, and API key abstraction. MCP gateways manage agentic interactions — tool discovery, access control, and multi-step workflow orchestration. As AI agents move beyond text generation to executing actions across systems, the distinction matters for governance and security. The post concludes with a pitch for Cequence AI Gateway, which claims to unify both capabilities into a single enterprise platform with OAuth 2.1 auth, sensitive data protection, and a trusted MCP registry.

LLM Proxies vs. MCP Gateways: What’s the Difference?

Enter: The Cequence AI Gateway – The Enterprise Solution