Understand Your Square Sales — Improvado MCP

Organizations with multiple Square locations have to download separate transaction reports for each location and manually combine them to get a consolidated view. This happens every time leadership asks for a cross-location summary — which is often.

Improvado aggregates data from all Square locations under one MCP endpoint. Your AI agent returns consolidated or location-specific results in a single query — no CSV merging, no manual reconciliation.

Square's inventory tracking updates with a delay and doesn't proactively alert teams when fast-moving items are running low. Stockouts happen because no one checked the dashboard at the right time — leading to missed sales and frustrated customers.

Improvado monitors Square inventory data continuously. The MCP server lets your AI agent set automated low-stock thresholds and alert the right person before an item runs out — turning reactive restocking into proactive management.

Understanding why refunds happen requires manually reviewing individual transactions in the Square dashboard. There's no built-in aggregation by reason code, product, or location — so refund trends go unnoticed until they've cost significant revenue.

Improvado normalizes Square transaction and refund data into a structured model. Your AI agent can aggregate refunds by reason, product, time period, and location — surfacing patterns that indicate product issues, staff training gaps, or fraud.