Scrapingdog vs Crawlora MCP

accor_amenities

Accor amenity reference catalog. Returns the anonymous public Accor amenity catalog with stable amenity codes, labels, categories, and display ordering. It is reference data for interpreting hotel search facets; booking, rates, rooms, reviews, and account data are excluded.

accor_brands

Accor brand directory. Returns the Accor brand directory published on the public brands page, with each brand's name, slug, and source URL. Booking, rates, rooms, reviews, contacts, and location are excluded.

accor_catalog_hotels

Search the Accor hotel catalog. Searches Accor's anonymous public hotel catalog by text, hotel code, or latitude/longitude radius. Results contain static property identity and broad location metadata plus catalog relevance/distance; contact details, precise hotel coordinates, payment, loyalty, media, rates, rooms, reviews, and booking data are excluded.

accor_destination_hotels

Accor hotels in a destination. Returns the static list of hotels published on one Accor destination directory page (world, continent, country, region, department, city, district, or place), optionally narrowed by a theme facet. Each hotel carries its code, name, source URL, and broad city/country. Booking, rates, rooms, reviews, contacts, and precise location are excluded.

accor_property

Accor hotel metadata. Returns static public metadata for one Accor hotel code, including name, brand, city/country, explicitly listed amenities, and published check-in/check-out times. Booking, rates, rooms, reviews, contacts, and precise location are excluded.

accor_search

Search Accor hotels. Searches the public Accor hotel index by destination or hotel name, with optional country, city, brand, star, page, and page-size filters. Results contain static hotel identity, location labels, ratings, and source URLs; booking, rates, rooms, reviews, loyalty, and payment flows are excluded.

accor_search_details

Accor place coordinates and viewport. Resolves an anonymous Accor search suggestion identifier to its description, coordinates, viewport, radius, and address components. It uses the same public place-details source as the Accor search box; booking, rates, rooms, reviews, and account data are excluded.

accor_search_suggest

Accor destination and hotel search suggestions. Returns anonymous Accor typeahead suggestions for a partial destination or hotel query, including destination/place and hotel identifiers, types, labels, and match metadata. It uses the public search-box suggestion source only; booking, rates, rooms, reviews, and result-list requests are excluded.

adidas_product

Get an Adidas product. Returns normalized product-detail data for one Adidas SKU: name, brand, category, description, pricing (current/standard/sale), images, and every purchasable size variant. product_id is the Adidas SKU (e.g. JI0397), taken from a search result's products[].id field or the trailing segment of an Adidas product page URL. An unknown product_id returns a not-found error.

adidas_product_review_topics

Get Adidas review topics for a product. Returns the topics an Adidas product model's customer reviews can be filtered by -- the "filter by topic" chips the product page shows, commonly satisfaction, comfort, color, purchase, fit, appearance, quality and style. Feed a topics[].topic value back to /adidas/product/reviews as its topic parameter to return only reviews about that aspect. The topic vocabulary is per model, not a fixed list: a shoe exposes fit and comfort topics that an accessory does not, so read it per model rather than hard-coding it. model_number is the Adidas model number (e.g. SAMBAU2312) -- NOT the SKU: take it from an adidas_search result's products[].model_number field. A model with no reviews, including a well-formed but unrecognized model_number, returns an empty topics list rather than an error. Note the label field is a display form of topic, not translated text: Adidas returns the same English values for every locale on this route.

adidas_product_reviews

Get Adidas product reviews. Returns one page of customer reviews for an Adidas product model, plus the model's rating summary: overall rating, star histogram, percentage of reviewers who recommend it, per-attribute averages (Size, Width, Comfort, Quality with their own scale labels), and Adidas's AI-generated review digest when one exists. Each review carries the rating, headline, body, author nickname, purchased colorway, helpful/not-helpful vote counts, badges, customer photos, and submission time. model_number is the Adidas model number (e.g. SAMBAU2312) -- NOT the SKU: take it from an adidas_search result's products[].model_number field, which is a different value from products[].id. Reviews are returned 10 per page. Reviews are scoped to review text written in the requested locale's language, and most of the US catalog's reviews are English, so a non-English locale commonly returns rating statistics and a localized summary with an empty reviews list. A model with no reviews -- including a well-formed but unrecognized model_number -- returns an empty reviews list rather than an error, because Adidas answers 200 with a zero count rather than 404.

adidas_search

Search or browse Adidas products. Searches Adidas.com product listings by keyword, or browses a category listing by taxonomy slug, with real pagination and sort options. Exactly one of query or category is required. Returns normalized product summaries (title, price, rating, images, color variants) plus facet filter groups, sort options, and (for category browse) a breadcrumb trail. Keyword search is best-effort relevance, not a guaranteed match: an obscure keyword returns whatever Adidas's own search index surfaces. A genuinely empty keyword search returns an empty product list, and requesting a page beyond the available result pages (or an unknown category) returns a not-found error. Category values are the path segment after /us/ in an Adidas category URL (e.g. women-athletic_sneakers); they can also be read from the url fields of a search/category response's own filters and breadcrumbs. Facets are applied by composing them into the category slug rather than by a separate parameter: each filters[].values[].slug is a token you splice into the category value (e.g. category=women-black-athletic_sneakers applies the Color=Black facet, and category=women-athletic_sneakers-prime applies Shipping=PRIME). Use filters[].key (the facet's stable name, e.g. searchcolor) rather than filters[].id, which is an opaque per-deployment UUID that cannot be used to build a request. Note the token's position within the slug varies by facet, so compose from a slug you have seen rather than assuming a fixed order.