amazon_get_bulk_search_volume
ChatGPTFetches Amazon search volume for up to 1,000 keywords in a single call — a bulk screening tool for ranking a whole shortlist of product ideas by demand at once, rather than calling get_demand separately for each one. Use this when a user has a list of candidate product names or keywords and wants to quickly see which ones have the most search volume before deep-diving on the top few with get_demand, get_price, or get_competition. Unlike every other tool here, cost is not fixed — it scales with how many keywords are supplied (roughly $0.012 plus $0.00012 per keyword, rounded up to the nearest 5 credits), so a 5-keyword call costs far less than a 500-keyword call. Charged only if usable data comes back.
amazon_get_offers
ChatGPTLists every current seller offer on one Amazon listing: each offer's price, condition (new or used), Prime eligibility, fulfillment type (FBA or FBM), buy-box-winner flag, and position. Use this when a user asks how contested the Buy Box is on a specific ASIN, how many sellers are competing on one listing, or wants the FBA/FBM split for that listing — needs an ASIN. This is distinct from get_competition, which gives the market-wide aggregate across many listings, and from amazon_get_seller_details, which gives one seller's profile across all their listings; neither of those shows per-offer detail on a single listing the way this does. Costs 35 credits, charged only if usable data comes back.
amazon_get_product_competitors
ChatGPTFinds other Amazon ASINs that genuinely compete with a given listing — products that share real search-result placements for the same keywords, not just products in the same category or with a similar title. Each result includes the competing ASIN, its average rank position, and how many keywords it shares with the original listing. Use this when a user asks who their real competitors are for a specific listing, or wants a competitor set anchored on actual keyword overlap rather than a category guess; it needs an ASIN, so the product must already be listed. Costs 10 credits, charged only if usable data comes back.
amazon_get_product_details
ChatGPTLooks up one live Amazon listing by its ASIN: current price and currency, availability status, star rating and rating count, full category breadcrumb path, best-seller rank(s) per category, whether it has A+ (enhanced brand) content, and its feature bullet points. Use this when a user already has an ASIN — their own listing or a competitor's — and wants a snapshot of how it looks right now; it is for an active, already-listed product, not a pre-launch idea (use get_demand/get_price/get_competition for those). For a listing's full seller/Buy Box detail, use amazon_get_offers instead; this tool covers listing content and standing, not who's selling it. Costs 35 credits, charged only if the ASIN resolves to real listing data.
amazon_get_purchase_signals
ChatGPTReads real purchase-frequency signals for the top Amazon listings matching a keyword: Amazon's own "bought in past month" badge count (a figure Amazon displays directly, not an estimate derived from rank), plus whether each listing carries the Amazon's Choice or Best Seller badge, along with its price, rating, review count, and sponsored-placement flag. Use this when a user wants to know which listings in a market are actually selling — not just which ones rank highest — for example "which of these products are really moving units". Takes a plain keyword, not an ASIN, and fetches live; nothing needs to be searched first. This is the cheaper default over amazon_search_products for the same kind of question — reach for that one instead only if you specifically need every listing on the page (not just the top 20 ranked ones) or a listing's image/URL. Costs 5 credits, charged only if usable data comes back.
amazon_get_rank_overview
ChatGPTGives an at-a-glance summary of how well an Amazon ASIN ranks across keywords: how many keywords land in each position bucket (#1, #2-3, #4-10, #11-100), reported separately for organic results and paid (ad) placements, plus total keyword count and total search volume per bucket. Use this when a user wants a quick health check on a listing's overall search visibility — "how is this product ranking overall" — rather than the full keyword-by-keyword breakdown; for that level of detail use amazon_get_ranked_keywords instead, which costs more and lists every keyword individually. Needs an ASIN, so the product must already be listed. Costs 5 credits, charged only if usable data comes back.
amazon_get_ranked_keywords
ChatGPTLists every keyword an Amazon ASIN currently ranks for organically — up to 100 keywords (a reverse ASIN lookup), each with its search volume, the ASIN's rank position for it, the listing's own title/price/rating/review count as it appeared on that keyword's results page, its Amazon's Choice/Best Seller badges and delivery message, an estimated cost-per-click, and a monthly search history spanning several years. Peak search month and season impact (Low/Moderate/High) are calculated from that history, not directly reported figures — read them as estimates. Use this when a user asks what keywords their (or a competitor's) live listing actually ranks for, or wants the full keyword-by-keyword detail behind a listing's search visibility; it needs an ASIN, so the product must already be listed on Amazon. For the aggregate summary instead of the full list (how many keywords fall into each rank-position bucket), use amazon_get_rank_overview, which is cheaper and answers "how am I doing overall" rather than "which exact keywords". Costs 20 credits, charged only if usable data comes back.
amazon_get_related_keywords
ChatGPTExpands a seed keyword into adjacent product and niche ideas using Amazon's own "related searches" data — not phrase variations of the same term, but genuinely different but related product concepts (e.g. "knee pillow" → "leg spacer pillow", "hip alignment pillow"). Use this when a user wants keyword-driven product ideas branching off a starting term, or is looking to widen a niche search before picking specific ideas to validate with get_demand. Pairs well with amazon_get_purchase_signals and amazon_get_bulk_search_volume as an idea-generation entry point. Takes a plain seed keyword, not an ASIN. Costs 10 credits, charged only if usable data comes back.
amazon_get_seller_details
ChatGPTRetrieves an Amazon third-party seller's public storefront profile by their seller id: business name, average rating, lifetime and 90-day feedback percentages (positive/neutral/negative), and a preview of other products they sell. Use this after get_competition surfaces a sellerId in its topSellers list, or when the user already has a seller id and wants to know more about who they're competing against — for example "who is this seller" or "tell me about seller A1B2C3". Do not use this for a specific product listing's Buy Box contest; use amazon_get_offers for that instead. Costs 65 credits, charged only when seller data actually comes back — a seller id that resolves to nothing costs nothing.
amazon_search_keywords
ChatGPTExpands a seed keyword into a table of related search terms, each with its own search volume, cost-per-click, a ranking-challenge score, and a monthly search trend (peak month, season impact). This is the tool for "what keywords should I target and how hard is each one" — different from get_demand, which only ever surfaces the ONE head term's own numbers plus a short related-keyword list capped at 20; and different from amazon_get_related_keywords, which returns Amazon's own "related searches" strings (genuinely different product concepts, no volume/CPC/difficulty per suggestion) rather than metrics on search-term variants of the seed. Use this when a user wants to prioritize which keyword variants to target, not just discover adjacent product ideas. Takes a plain seed keyword, not an ASIN. Costs 10 credits, charged only if usable data comes back.
amazon_search_products
ChatGPTRuns a live Amazon search for a keyword and returns EVERY listing on the results page (not just the top 20), including each listing's product image and outbound link: ASIN, title, price, rating, review count, brand, sponsored-placement flag, image URL, listing URL, and Amazon's own "bought in past month" badge where shown. Costs 35 credits — 7x amazon_get_purchase_signals — so prefer that cheaper tool by default; reach for this one specifically when a user wants the image/link to browse or share a listing, or the full results page rather than just the top 20 ranked ones. amazon_get_purchase_signals is the better default for "is anyone buying this" / "what's ranking" questions: same asin/ title/price/rating/reviewCount/boughtPastMonth/sponsored fields, plus Amazon's Choice and Best Seller badges this tool doesn't carry, for roughly a seventh of the cost. get_competition/get_price answer market-wide aggregate questions about the same term, not individual listings, so neither substitutes for either of these. Each result's ASIN can feed amazon_get_offers, amazon_get_product_details, or amazon_get_seller_details for a deeper look at one listing. Takes a plain search keyword, not an ASIN. Charged only if usable data comes back — an empty results page is still a successful, charged answer.
browse_categories
ChatGPTBrowses a general product-category taxonomy (a vertical classification of markets, not Amazon's own browse-node tree) for open-ended ideation — call with no arguments to list top-level categories, or pass a categoryCode from a previous result to drill into its children. Use this when a user wants to explore what product categories or sub-niches exist under a broad area before picking a specific idea to research further with get_demand, get_price, or get_competition — it is a standalone discovery aid, not a filter any other tool accepts. Do not use this to look up a specific product's own category; amazon_get_product_details returns that product's actual categoryPath instead. Free — costs no credits regardless of how many times it's called.
get_ad_activity
ChatGPTChecks live paid-search advertising activity for a not-yet-listed product idea: how many advertisers are actively bidding on the term, how many shopping ad results appeared, and a list of the advertisers themselves (domain, ad title, position, display URL). Use this when a user asks how competitive paid ads are for a product idea, whether it's worth running ads, or who is already advertising against a keyword — it takes a plain product name and fetches live; nothing needs to be searched or saved first. Coverage is partial by design (desktop search ads in one region only) — always read the returned coverageNote before concluding an empty advertiser list means nobody advertises; it may just mean this coverage slice missed them. Costs 5 credits, charged only if usable data comes back.
get_bulk_search_volume
ChatGPTDeprecated alias for amazon_get_bulk_search_volume, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_bulk_search_volume directly — see its description for what this returns and when to use it.
get_competition
ChatGPTChecks the live competitive landscape for a not-yet-listed product idea: brand concentration (distinct brand count, top-brand and top-5-brand market share, HHI concentration index), total seller and independent-store counts, a ranked list of top sellers by estimated monthly revenue (each with a sellerId), and the top independent online stores selling into this market. Use this when a user asks how crowded or saturated a market is, who the market leaders are, or wants a sellerId to drill into with amazon_get_seller_details — it takes a plain product name and fetches live; nothing needs to be searched or saved first. This is the only tool that produces a sellerId; there is no other way to reach amazon_get_seller_details except a seller id the user already has. The most expensive tool here at 185 credits, because resolving who sells each listing is the priciest call this connector makes; charged only if usable data comes back.
get_demand
ChatGPTChecks live market demand for a not-yet-listed product idea: monthly search volume, cost-per-click (CPC), a keyword-difficulty score and label, the search-interest trend slope, an overall competition index, and a list of related keywords with their own volume and difficulty. Use this first when a user asks whether there is demand for a product idea, how popular a search term is, or wants to validate a product before researching price or competition — it takes a plain product name (e.g. "knee pillow") and fetches live; nothing needs to be searched or saved first. Do not use this for an Amazon listing that already exists; amazon_get_ranked_keywords and amazon_get_rank_overview answer that for a known ASIN instead. Costs 10 credits, charged only if usable data comes back.
get_offers
ChatGPTDeprecated alias for amazon_get_offers, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_offers directly — see its description for what this returns and when to use it.
get_price
ChatGPTChecks live pricing for a not-yet-listed product idea across marketplace channels: median, minimum, and maximum price, total listing count, and a per-channel breakdown (each channel's own price range, listing count, average rating, median review count, and best-seller rank where available). Use this when a user asks how much a product typically sells for, what price range to target, or wants to compare pricing across channels for an idea — it takes a plain product name and fetches live; nothing needs to be searched or saved first. Do not use this for one already-known Amazon listing's exact price and availability; use amazon_get_product_details for that instead. Costs 35 credits, charged only if usable data comes back.
get_product_competitors
ChatGPTDeprecated alias for amazon_get_product_competitors, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_product_competitors directly — see its description for what this returns and when to use it.
get_product_details
ChatGPTDeprecated alias for amazon_get_product_details, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_product_details directly — see its description for what this returns and when to use it.
get_purchase_signals
ChatGPTDeprecated alias for amazon_get_purchase_signals, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_purchase_signals directly — see its description for what this returns and when to use it.
get_rank_overview
ChatGPTDeprecated alias for amazon_get_rank_overview, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_rank_overview directly — see its description for what this returns and when to use it.
get_ranked_keywords
ChatGPTDeprecated alias for amazon_get_ranked_keywords, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_ranked_keywords directly — see its description for what this returns and when to use it.
get_related_keywords
ChatGPTDeprecated alias for amazon_get_related_keywords, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_related_keywords directly — see its description for what this returns and when to use it.
get_seller_details
ChatGPTDeprecated alias for amazon_get_seller_details, kept only so connections made before that rename keep working. Same inputs, same output, same cost. New integrations should call amazon_get_seller_details directly — see its description for what this returns and when to use it.
get_trends
ChatGPTChecks live trend and interest signals for a not-yet-listed product idea: the search-interest slope (rising, flat, or falling) with a confidence label (measured, estimated, or unavailable), total social mention volume and its velocity ratio, and whether the topic currently looks like a breakout with an estimated growth percentage and category. Use this when a user asks if a product idea is trending, gaining or losing interest, or might be a breakout opportunity — it takes a plain product name and fetches live; nothing needs to be searched or saved first. When interest is estimated from mention volume rather than measured search data, the search-interest-slope field is intentionally left blank rather than guessed — check interestConfidence to know which case applies. Costs 20 credits, charged only if usable data comes back.
