# ads_get_refinements_for_category (https://sellersheetai.com/docs/mcp-api/tools/ads_get_refinements_for_category)

> Sponsored Products: the refinements (brand / age-range / genre facets) targetable WITHIN a category — e.g.

Access: **READ** · toolset amazon_ads · family ads.sp

"Toys > Building Sets" refined to brand=LEGO. Amazon Ads API · getRefinementsForCategory · GET /sp/targets/category/{categoryId}/refinements Docs: https://advertising.amazon.com/API/docs/en-us/sponsored-products/3-0/openapi/prod#tag/Product-Targeting/operation/getRefinementsForCategory

## Call it

MCP tool call:

```json
{
  "name": "ads_get_refinements_for_category",
  "arguments": {
    "store": "myStore-US",
    "countryCode": "<countryCode>",
    "categoryId": "<categoryId>"
  }
}
```

Tool API (early access — contact us):

```bash
curl -X POST https://api.sellersheetai.com/api/v1/tools/ads_get_refinements_for_category \
  -H "Authorization: Bearer $SELLERSHEET_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"store":"myStore-US","countryCode":"<countryCode>","categoryId":"<categoryId>"}'
```

## Arguments

| Name | Type | Required | Description |
|---|---|---|---|
| `store` | string | yes | the store ref `<store>-<CC>` (name-country, e.g. 'myStore-US') — one of get_user_context's store_refs, verbatim. |
| `countryCode` | string | yes | the Ads profile's 2-letter country code (e.g. 'US'). |
| `categoryId` | string | yes | from ads_get_category_recommendations_for_asins (or the catalog browse node). |
| `locale` | string |  | the language of the returned facet names; omit for the marketplace's default language. Allowed: ar_AE \| de_DE \| en_AE \| en_AU \| en_CA \| en_GB \| en_IN \| en_SG \| en_US \| es_ES \| es_MX \| fr_CA \| fr_FR \| hi_IN \| it_IT \| ja_JP \| ko_KR \| nl_NL \| pl_PL \| pt_BR \| sv_SE \| ta_IN \| th_TH \| tr_TR \| vi_VN \| zh_CN. Allowed: ar_AE \| de_DE \| en_AE \| en_AU \| en_CA \| en_GB \| en_IN \| en_SG \| en_US \| es_ES \| es_MX \| fr_CA \| fr_FR \| hi_IN \| it_IT \| ja_JP \| ko_KR \| nl_NL \| pl_PL \| pt_BR \| sv_SE \| ta_IN \| th_TH \| tr_TR \| vi_VN \| zh_CN. |

## Result

- Amazon's payload in data.result.

## Gotchas

- data.result.brands / ageRanges / genres are the facet ids to build the target with (ageRanges / genres may be null).
- Best practice: build the target with ads_create_target, targetType='PRODUCT_CATEGORY', targetDetails= {"productCategoryTarget": {"productCategoryRefinement": { "productCategoryRefinement": {"productCategoryId": "<this categoryId>", "productBrandId"?, "productAgeRangeId"?, "productGenreId"?}}}} — keep only the facets you actually want to narrow by (productCategoryRefinement is nested TWICE — the outer key is the wrapper, the inner one holds the fields).