Systems | Development | Analytics | API | Testing

This is part one of a series exploring how Kong AI Gateway can be used in an AI Agent development with LangGraph. The series comprises three parts.

The Model Context Protocol (MCP) is quickly becoming a foundational layer for AI systems. It enables large language models and AI agents to interact with external tools and data sources over standardized JSON-RPC interfaces. By doing so, MCP transforms how intelligent applications consume APIs. Reading local files, controlling IoT devices, orchestrating backend workflows—MCP servers act as structured gateways between AI and your business logic.

With the EU AI Act now in force, compliance is no longer about aspirational ethics or last-minute checklists, it’s about operationalizing quality assurance at every stage of your AI lifecycle.

Imagine a world where every backend, legacy system, cloud database, and app is instantly connected—no manual coding, no ongoing maintenance headaches. As businesses rush to unlock value from data, API gateways are becoming critical infrastructure. The most advanced platforms now go beyond traditional API management—bringing AI, automation, and security into the integration layer.

Enterprise automation didn’t start with AI agents, but they’ve had a much bigger impact than earlier automation methods, such as software scripts or bots. Modern AI agents can do a lot more than tackle repetitive tasks. They can reason through complicated workflows, choose the best course of action, and access tools to execute said action. But to do all this, AI agents require interoperability. They need to be able to connect to numerous tools, databases, services, and APIs.

We’re excited to announce the release of DreamFactory 7.1.1 — a milestone update that lays the foundation for AI-powered data integration while continuing to build on our mission of secure, no-code API generation.