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 AI coding and Agent Harness approach is no longer experimental. This is likely the most impactful agentic AI use case in production today, and Claude Code is one of the solutions really leading the charge. But as engineering teams race to adopt Claude Code across their organizations, a critical…
Your traditional monitoring dashboards may show perfect infrastructure health, but that doesn't guarantee your large language model (LLM) application is running correctly. AI observability is the crucial fourth pillar that adds behavioral telemetry to detect and troubleshoot unique issues like…
Last week, Gartner published a report titled MCP Servers Will Fuel the Next AI Revenue Surge — Context as a Service (1) that should be required reading for every enterprise technology leader. Then, Kong CEO Augusto Marietti (Aghi for short) wrote out his thoughts on the subject and why context is…
AI agents are spreading across organizations rapidly. Each agent needs secure access to different Model Context Protocol (MCP) servers. Authentication becomes complex. Scaling creates bottlenecks. The dreaded "too many endpoints" problem emerges. You face a classic AI infrastructure headache. The…
The promise of agentic AI is clear: autonomous systems that can reason, plan, and act on your behalf. But there's a fundamental problem standing between that vision and enterprise reality: agents need context to make decisions, and that context lives scattered across your organization. Context is…
In today's digital landscape, APIs are the backbone of modern applications, and AI is the engine of innovation. As organizations increasingly rely on microservices and AI-powered features, the API gateway has become the critical control point for managing traffic. But as LLM/GenAI and MCP requests…
For too long, the Model Context Protocol (MCP) has operated on a principle of open access: connect an AI agent to an MCP server, and it gets access to every single tool that server offers. While this approach is simple for initial experimentation, it quickly becomes a liability in production.…
In the rapidly evolving landscape of AI-driven development, the Model Context Protocol (MCP) has emerged as the critical standard for connecting AI applications to the data and tools they need. We are excited to announce the Technical Preview (TP) of Kong MCP Registry , a major milestone in our…
Modern AI applications are no longer just about sending prompts to an LLM and returning text. As soon as AI systems need to interact with real business data, internal APIs, or operational workflows, the problem becomes one of orchestration, security, and control. The challenge is to build secure AI…
The agentic era is here, and it's exposing a critical gap in enterprise infrastructure. AI agents are no longer experimental. As many as 9 out of 10 enterprise organizations are actively adopting AI agents. Agents are making autonomous decisions, orchestrating complex workflows, and interacting…
Kong AI Gateway 3.13 introduces MCP Tool ACLs , a powerful feature that enables fine-grained authorization and granular security policies for individual AI agent tools, solving the 'all-or-nothing' access problem. The evolution of AI agents and autonomous systems has created new challenges for…
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…
While AI is revolutionizing the future of nearly every industry, it’s also created a unique set of challenges and liabilities that will need to be addressed as the area grows. Enter AI governance: a set of rules and best practices to ensure that AI is used effectively, securely, and responsibly.…
Kong AI Gateway 3.13 moves enterprises from AI experimentation to shipping production-grade agents by unlocking new capabilities focused on agentic security, developer productivity, and resilience, including MCP tool-level access control, expanded provider support, and smarter load balancing. We…
The rise of intelligent agents and AI prompts is transforming APIs from mere infrastructure into the capability ecosystem of the agentic era, driving a new model of ecosystem-led growth . To prepare for the inevitable explosion of agent-driven API traffic, enterprises are prioritizing a strategic…