Improvado MCP extracts data from Google Tag Manager and makes it queryable by AI agents. Ask about container health, tag configurations, and trigger logic without navigating GTM manually.
Improvado MCP connects GTM data to AI, so teams can audit containers, review tag configurations, and check trigger logic in plain English — no manual browsing through nested menus.
"Which tags fired on checkout pages last week?"
1 hr → 1 min"List all triggers associated with conversion tags"
Manual → auto"Are there any tags without firing conditions set?"
45 min → 30 secPush tag updates, modify triggers, and publish container versions directly from your AI agent — acting on audit findings without switching to the GTM interface.
"Add a pageview tag to all product listing pages"
2 hrs → 5 min"Disable deprecated tags in the staging container"
Manual → auto"Update conversion tag trigger to exclude internal traffic"
1 hr → 3 minMonitor tag firing rates, container publish history, and tracking anomalies continuously — your AI agent flags issues before they corrupt conversion data.
"Alert if any conversion tag stops firing"
Manual check → auto"Track container publish frequency across workspaces"
Manual → auto"Show tags with firing rate drops above 30% this week"
Weekly audit → instantYour AI agent doesn't just surface data — it acts. Adjust pricing, update product descriptions, manage inventory, apply discounts — all through natural language. The MCP server translates intent into API operations.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
One conversation. All six phases. Every platform.
Auditing GTM containers manually means clicking through dozens of tags, triggers, and variables — a process that takes hours for large implementations.
Improvado MCP extracts the full container structure, letting AI agents surface configuration issues in seconds.
Tags stop firing or fire incorrectly without any visible alert — teams only discover data gaps weeks later during reporting.
Continuous AI monitoring tracks firing rates and configuration changes, flagging anomalies the moment they appear.
Multiple teams publishing to the same container creates conflicts, duplicate tags, and broken triggers that are hard to trace.
AI agents query the full publish history and configuration state, surfacing conflicts and duplicates before they reach production.
Same MCP connection, different workflows for every team member. Each role asks in natural language — the MCP server handles the complexity (rate limits, auth, schema normalization, governance) behind the scenes.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
