We wanted an AI agent to manage a real production app (its content, its catalog, its push notifications) natively, not through screenshots and simulated clicks. So we built an MCP server. Here's the whole thing: why, how, a real session, and where it still falls short.
One line of context so the rest makes sense: GoodBarber is a no-code app builder (running since 2011). Customers configure an app in a web back office; the platform compiles native iOS and Android builds plus a PWA. The question we set out to answer: can an AI agent operate one of those apps, end to end, the way its owner does?
We already had APIs. That wasn't the point.
The platform has had APIs for years. Exposing endpoints was never the problem. The problem was that every "connect your assistant" integration is custom glue: tool definitions written for one vendor, an auth flow, retry logic, docs written for a model to read. Then you do it all again for the next assistant. The classic N×M integration mess: N assistants × M platforms.
The Model Context Protocol (introduced by Anthropic in November 2024, donated to the Linux Foundation in late 2025) standardizes exactly the parts we kept rewriting:
