Discover the future of intelligent API traffic management. Learn how AI-powered gateways enable smarter routing, adaptive security, and real-time decision-making to optimize and secure API ecosystems.
The first pillar is enablement. Developers need tools that reduce friction when building AI-powered applications and agents. This means providing: The goal isn't to replace existing development workflows but to extend them. Developers should be able to build agents using familiar paradigms while…
The evolution of AI agents and autonomous systems has created new challenges for enterprise organizations. While securing API endpoints is well-understood, controlling access to individual AI agent tools presents a unique authorization problem. Today, we're excited to announce a powerful solution…
In one of our posts, Kong AI/MCP Gateway and Kong MCP Server technical breakdown, we described the new capabilities added to Kong AI Gateway to support MCP (Model Context Protocol). The post focused exclusively on consuming MCP server and MCP tools through Kong MCP Gateway. Now, it's time to check…
AI governance establishes the principles, roles, processes, and controls for responsible AI deployment. It transforms abstract ethics into concrete practices. Think of AI governance as a rulebook for how to use AI in a secure, ethical, observable, moderated, and auditable fashion. It’s a…
We know that successful AI connectivity programs often start with an intense focus on how you govern and protect LLM and MCP traffic. This is why Kong was first to market with an enterprise-grade AI gateway , and it’s why, in our last release, we added enterprise MCP proxy support to our…
APIs have quietly powered the global shift to an interconnected economy. They’ve served as the data exchange highways behind the seamless experiences we now take for granted — booking a ride, paying a vendor, sending a message, syncing financial records, or stitching together SaaS tools into a…
Companies are charging headfirst into AI, with research around agentic AI in the enterprise finding as many as 9 out of 10 organizations are actively working to adopt AI agents. LLMs are being deployed, agentic workflows are getting created left and right, and the promises of what this technology…
In the latest Kong Gateway 3.12 release , announced October 2025, specific MCP capabilities have been released: The Kong AI Gateway sits in between the AI applications we build and the MCP Servers and GenAI models we consume. In fact, the Kong MCP Gateway sits side-by-side with the Kong LLM…
The Requirement : Article 10 of the EU AI Act mandates strict data governance for high-risk AI systems. This includes error detection, bias monitoring, and arguably most critically for enterprise use — ensuring that sensitive personal data (PII) is not improperly processed or leaked into public…
Kong Gateway is an API gateway and a core component of the Kong Konnect platform . Built on a plugin-based extensibility model, it centralizes essential functions such as proxying, routing, load balancing, and health checking, efficiently managing both microservices and traditional API traffic. An…
A close examination of what really powers the AI prompt unveils two technologies: the large language models (LLMs) that empower agents with intelligence and the ecosystem of MCP tools to deliver capabilities to the agents. While LLMs make your agents smart, it would be hard to provide agents with…
The Gateway Evolution An unoptimized AI inference endpoint can burn through thousands of dollars in minutes. This isn't hyperbole. It's the new reality of artificial intelligence operations. When GPT-4 processes thousands of tokens per request, traditional infrastructure crumbles. The demands are…
Data might be the fuel for AI. But APIs are the proper way to package that “fuel” as AI-ready “food” is through the API. AI coding tools can do a lot without APIs, but at some point they’ll need to be able to: . . . and all ideally without the engineer having to…
The solution landscape is complicated by the fact that MCP is still finding its footing, and there are many various OSS projects and vendors that are rapidly shipping “MCP support” in an attempt to take advantage of the hype and attention around MCP. Unfortunately, many early attempts at solutions…
While building a GenAI-powered agent for one of our company websites, I integrated components like LLM APIs, embedding models, and a RAG (Retrieval-Augmented Generation) pipeline. The application was deployed using a Flask API backend and secured with API keys. However, post-deployment, several…
Organizations are gradually realizing that API and AI observability aren't two separate problems; they're intertwined and require unified solutions. Without waiting on engineering, it's hard to answer simple questions like "Who's using my APIs?" or "Which APIs are causing the most issues?" Now…
Secure your AI infrastructure with prompt guards, PII sanitization, and centralized governance. Control LLM costs with token-based rate limiting and semantic routing across providers.