Google Merchant Center via Windsor.ai

Windsor.ai pulls Google Merchant Center product feed and Shopping data. The connector id is google_merchant. Pass google_merchant as the connector on every tool call; the Windsor.ai server serves all connectors, so it is never implied.

This connector is read-only product feed and Shopping analytics. It has no Google Ads Shopping campaign data (spend and ROAS live in the Google Ads connector, so route those questions there), and it does not edit the product feed or fix disapproved products — there are no write actions. If asked to change GTINs, prices, or other feed data, say that's out of scope here.

Golden rules:

• Never guess field, account, or option names — get them from get_fields, get_connectors, and get_options. Call those first.
• Read-only connector; there are no live write actions to run.
• Report what the user asked for, concisely.

1. Ground yourself first

Call get_connectors to see which Merchant Center accounts are connected (each has an id and, usually, a name). If none is connected, help the user connect one: call get_connector_authorization_url (or get_connector_connect_info for the auth type and steps) and give them the setup link — do not describe manual dashboard navigation.

If the user names an account, match it to a connected account id. If several are connected and the request is ambiguous, ask which account.

2. Reading Merchant Center data

1. Call get_fields for google_merchant to get valid field ids — product and feed attributes (product status, disapproval reasons/issues, availability, price, price benchmark, brand, category) and Shopping performance metrics (clicks, impressions, CTR). Use the exact ids returned, not these examples.
2. If the analysis needs segmentation or attribution controls, call get_options to see the connector's options and valid values.
3. Call get_data with:
   • fields: the ids you actually need (keep the set small).
   • accounts: the target account id(s); omit for all connected accounts.
   • A date range: either date_from/date_to ("2026-02-01"), or date_preset — last_7d, last_30d, this_month; append T to include today (e.g. last_7dT, this_monthT).
   • filters: optional conditions, e.g. filtering to disapproved products or to a price-benchmark threshold; combine with "and"/"or" as needed.

Merchant Center specifics to respect:

• Feed/status attributes (approval status, disapproval reasons, availability, price, price benchmark) describe the current state of the feed, while clicks, impressions, and CTR are per-day performance metrics over the requested range. Don't present a current feed attribute as if it varied over a historical date range.
• When surfacing disapprovals, include the issue/reason field alongside the product so the user knows what to fix — even though this connector can't fix it for them.

Common requests → recipe:

• Disapproved products: fields for product, status, and disapproval issues; filter to the disapproved status.
• High impressions, low CTR: fields for product, impressions, clicks (or CTR), over a date range; rank by impressions and CTR in your answer.
• Price benchmarking: fields for product price and price benchmark; compare and flag products priced above or below benchmark.

If a field the user wants isn't in get_fields, say so rather than substituting a different metric. There is no ad spend or campaign data here.

3. Reference real data, don't fabricate

On an error (unknown field/connector/account), call the relevant discovery tool and retry with correct ids, or report the specific error. Never invent product statuses, disapproval reasons, click or impression counts, or price figures.