Systems | Development | Analytics | API | Testing

Get Started With MCP Proxies on WSO2 Platform AI Gateway

Deploy an MCP server through WSO2 Platform AI Gateway in a few commands — running entirely on your own infrastructure. This quickstart shows you how to set up MCP proxies on WSO2 Platform AI Gateway as a standalone component via Docker. You'll start a sample MCP server, deploy it as an MCP proxy configuration to the gateway, and verify it using the official Model Context Protocol Inspector. What you'll cover.

AI Coding Tools and API Governance: Here's Why You Need Both.

GitHub Copilot, Claude, and Cursor have become genuine superpowers for API development. They draft OpenAPI definitions, generate endpoints, propose schema changes, and write test cases — all from inside the IDE, in real time. Teams using these tools are generating API definitions faster than most thought possible even a few years ago. That velocity is real, and it’s reshaping how engineering teams think about their toolchain.

Is AI making your teams better, or just busier?

AI adoption programs tend to end in the same place. Tools are accessible, usage is up, and there's a dedicated Slack channel for wins. Six months later, nothing about how the team works has fundamentally changed. People are doing the same things – just slightly faster. And it’s easy for programs to stall when you’re measuring the wrong thing. Adoption (whether people have access and whether they're using the tools) is visible and easy to report.

AI Agents Deployed, but what about cost optimization?

AI agents are no longer a pilot-stage bet. As of 2026, 80% of enterprises have at least one production AI agent deployed. The global AI agents market has crossed $10.91 billion and is sprinting toward $52.62 billion by 2030. The cost-per-task economics are staggering: a human-handled customer support ticket costs $4.18 on average. An AI agent resolves the same ticket for $0.46. That is a 9x cost reduction, right there.

How durable sessions unify human-to-human and human-to-agent messages

AI chats are often a rather solitary experience: just you and ChatGPT, sitting there together, solving a problem. But so many of the tasks that we perform day to day are ones that benefit from, or often even require, collaboration with other people such as colleagues, family members, or friends. So, if AI agents are helpful, and other people are helpful, then how can we provide a space for multiple people to collaborate with each other and with AI agents?

Build resilient end-to-end tests with AI agents in SmartBear Reflect | Demo Den

See how SmartBear Reflect uses agentic AI to build end-to-end tests in minutes and keep them resilient as your application changes. In under 20 minutes, Reflect co-creator, and SmartBear Director of Product Management, Todd McNeil walks through live test creation across web and mobile, with zero fluff.