A turbo model booked parking for the wrong day, and a stock-market agent reported a -2.21% drop that was really -0.26%. Both had the correct instructions written down. Both ignored them. Prompts are suggestions, not guardrails.
Most apps you rely on were never meant to be automated. They have a tap-here-tap-there UI for humans, a private backend, and no API in sight. This is about wrapping one of them — our office parking platform — as an MCP skill an AI agent can drive on its own, at midnight, every night. Eight tools. Eight failed payload guesses. Three independent ID spaces hiding behind every booking. And one bypass that really shouldn’t have worked.
The parking part is incidental. By the end you’ll have a recipe that works on the gym-booking site, the restaurant reservation page, the internal approval tool — anything with a web or mobile surface.
What if you could just say “reserve parking for tomorrow” to your AI tool and have it actually happen? We built a MCP server in one Python file (~650 lines, zero frameworks) that does exactly that. Setup time: under 5 minutes. Dependencies: two pip packages. And now any MCP-compatible AI tool — OpenCode, Claude Desktop, whatever — can check, create, and cancel our office parking reservations through natural language.