We’re thrilled to announce the winners of the 5th Annual Kong Hackathon, held in conjunction with API Summit 2025.
We challenged solo hackers and full-stack teams worldwide to create projects that don’t just react, they think, adapt, and act autonomously. Clearly, this year's theme was agentic AI: solutions that take initiative, make decisions, and solve real-world problems without being told what to do at every step.
The hackathon participants built projects that connected intelligent agents with real-world infrastructure through the Kong AI Gateway, creating solutions that were innovative, practical, and production-ready.
The results are in! The top three projects listed below impressed the judges for creativity, technical depth, impact and use of Kong. Each one shows how agentic AI and API infrastructure are shaping the next wave of intelligent automation.
By: Abhishek Chauhan and Preesha Gehlot
The Session History Plugin extends the Kong AI Gateway with persistent session objects that preserve conversation history across requests using the x-ai-session-id header.
By integrating MongoDB for storage and implementing context summarization for efficient state management, the plugin enables scalable, context-aware conversational AI sessions.
It’s a thoughtful solution to one of the most common challenges in AI-driven applications: maintaining relevant context without sacrificing performance.
By: Satyajit Sial, Prema Namasivayam, Ritik Bhola, Akash Acharya, and Ashal Pearl Dsouza
The AgenticAI-MCP-Client plugin brings seamless Model Context Protocol (MCP) integration to Kong.
Connected to the Mongo MCP Server, it accepts natural language input, processes it through an LLM-powered agent, and converts it into structured queries.
By centralizing MCP connections within the Kong Gateway, the plugin reduces operational overhead, streamlines observability, and helps minimize the attack surface; it’s a big step forward in safely operationalizing AI systems.
By: Andrew Kew
The Kong auto rollback AI agent is an autonomous Site Reliability Engineering (SRE) tool designed to monitor gateway configurations for failures and automatically roll back misconfigurations.
This agentic approach to infrastructure management ensures rapid recovery and operational resilience — a practical example of using AI to strengthen DevOps workflows.
While each project took a unique approach, the winning entries shared a few common traits:
Congratulations to all the winners and participants on making this year’s hackathon successful.
These projects demonstrated creativity and technical excellence which truly manifests the innovative spirit of Kong’s developer community.
We especially thank the mentors, judges, and contributors for their support.
That’s a wrap on the Kong Annual Hackathon 2025. See you next year!
A decade ago, we set out to connect the world through APIs, which we saw as fundamental building blocks of software. Before Kong, we founded Mashape as the first API marketplace to provide an assembly line for developers building apps, and then we o
That’s a wrap on API Summit 2025 ! At our eighth annual event, the brightest minds in the worlds of APIs and AI gathered in New York City to define the next chapter of digital innovation. We're entering an era where APIs are not just connecting ser
Agents are ultimately decision makers. They make those decisions by combining intelligence with context, ultimately meaning they are only ever as useful as the context they can access. An agent that can't check inventory levels, look up customer his
MCP servers expose all tools by default. There are two problems with this: security (agents get capabilities they shouldn't have) and performance (too many tools degrade LLM tool selection). The solution? Put a gateway between agents and MCP server
The Kong MCP Registry acts as a central directory for AI agents and clients to access services that provide context or take action. For AI agents, think of it as a combination of a "Service Catalog" and a "Developer Portal." It offers the metadata,
Why Risk Management Will Separate Agentic AI Winners from Agentic AI Casualties Let's be honest about what's happening inside most enterprises right now. Development teams are under intense pressure to ship AI features. The mandate from leadership
AI spending is exploding across the organization—but often not in the ways leadership approved or finance can track. Development teams spin up LLM connections to ship features faster. Data teams provision GPU clusters for experiments that get abando