What makes this Gartner report so striking is that its recommendations — which are published independently and written for a broad enterprise audience — map almost perfectly onto Kong's platform architecture. Not directionally. Precisely. Aghi briefly touched on these points in his blog; allow me to expand on them a little further.
Gartner says enterprises need to "expose MCP servers by enabling publishing to registries in enterprise-managed AI gateways." That's Kong's AI management, which includes AI Gateway and Konnect MCP Registry. AI Gateway is purpose-built to govern, route, and manage traffic to and from LLMs, MCP servers, and AI agents. The Konnect MCP Registry enables teams to control which agents access which context, and under what conditions.
But here's what most vendors miss: the richest enterprise context doesn't originate in AI systems. It lives in the APIs and event streams that have been running your business for years: transactional records, behavioral signals, real-time operational data, and partner integrations.
Kong's API management stack already governs the API-driven context at massive scale across hundreds of enterprises. Kong's Event Management stack manages the streaming data layer — Kafka, webhooks, event-driven architectures — where real-time context is born and brokered. Together, Kong's three management layers (AI, API, and event) cover the spectrum of enterprise context: synchronous API traffic, asynchronous event streams, and AI-native traffic exposed over protocols such as MCP and agent-to-agent communication.
Gartner also says enterprises need to "facilitate easy discoverability and usage... drive a frictionless PLG motion focused toward developers." That's Kong's Developer Portal, where internal teams and external partners can discover, subscribe to, and begin consuming APIs, LLMs, events, and MCP Servers in a fully self-service motion.
But it’s not just controlling and opening up access to context. Gartner says the shift to the context economy requires orchestrating context across enterprises rather than defending it within walled gardens. That's Kong's Context Mesh, the new integration and runtime layer that lets enterprises unify the full AI data path across APIs, events, and AI-native protocols like MCP, so context flows where it needs to go without creating new security or governance gaps.
And then there's the piece every other vendor in this space simply cannot address.