Last week, I connected a GA4 MCP server to my AI coding workflow inside Google Antigravity IDE to test something I’d been thinking about for a while: What happens when your coding agent can inspect analytics data while you’re still working inside the codebase? Not after deployment. Not after checking dashboards later. While coding. I expected it to be mildly useful. Instead, the workflow surfaced suspicious traffic patterns, a discoverability issue tied to sitemap structure, and a dramatically faster way to validate event tracking implementations. More importantly, it changed how I think about analytics and development workflows. The Problem With Traditional Analytics Workflows Most web development workflows still separate: implementation, analytics, debugging, and optimization. The typical loop looks something like this: Build or modify something Deploy changes Open GA4 Check if tracking/data looks correct Form hypotheses Go back to the codebase Repeat It works, but it creates a lot of context switching.…