BigQuery MCP server: what an AI agent can query, and the guardrails it needs
Google's BigQuery MCP server gives an agent 9 tools, SQL on raw tables and up to 3,000 rows. It has no per-query byte cap and no metric definitions.
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Google's BigQuery MCP server gives an agent 9 tools, SQL on raw tables and up to 3,000 rows. It has no per-query byte cap and no metric definitions.
GA4 reads nine UTM parameters and treats values as case-sensitive text. Without one written convention, a single campaign splits across report rows.
ChatGPT data analysis is safe for exploring a spreadsheet and unsafe for deciding with it: the math is right, the revenue definition is a guess.
A lake keeps raw data, a warehouse keeps modeled data, a lakehouse puts transactions on open files. None of them defines net revenue.
The Google Analytics MCP server reads GA4 through the Data API, which follows your reporting identity. On Blended, the numbers arrive already modeled.
Google Ads counts purchases 30 days after a click; Meta, 7 days after a click or 1 after a view. Plug all three MCPs into Claude and one order counts twice.
Mollie says it plainly: the customer may not return. Your purchase event lives on the page they never reached.
Google lists BigQuery export among features that do not support behavioural modelling. The interface estimates; the export observes.
GA4's BigQuery export caps at 1 million events a day, and an exceeded export pauses without reprocessing previous days.
GA4 standard allows 2 or 14 months, and large properties get 2. The aggregate report survives; the exploration does not.
Adobe says it plainly: the two should not match in almost every case. GA4 excludes tax and shipping; Shopify includes both.
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