Apiguru Amazon Data vs TrustRails MCP Server
A side-by-side look at the Apiguru Amazon Data and TrustRails MCP Server MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Apiguru Amazon DataE-Commerce · Local subprocess (stdio)Live Amazon product, review, search, deal, offer/stock and seller data across 20 marketplaces.64GoodAuth: no auth requiredVerdict: choose Apiguru Amazon Data for e-commerce work as a local process; choose TrustRails MCP Server for e-commerce as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Apiguru Amazon Data when
- You need dedicated capabilities in the E-Commerce domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
product_details, product_reviews, search.
Choose TrustRails MCP Server when
- You need dedicated capabilities in the E-Commerce domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
TRUSTRAILS_API_KEY. - You want tools like
search_products, get_product.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | Apiguru Amazon Data | |
|---|---|---|
| Category | E-Commerce | E-Commerce |
| Quality signal | 64/100 · Good | 55/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | Not declared |
| Pricing | Freemium | Not declared |
| Required env vars | None listed | TRUSTRAILS_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 0 |
| Directory activity | 2 views 0 installs 0 upvotes | 2 views 0 installs 0 upvotes |
| Tools | 12 | 2 |
| Full listing | View Apiguru Amazon Data | View TrustRails MCP Server |
Tools & capabilities
Apiguru Amazon Data tools 12
product_detailsUse for one product's current listing. Not for several ASINs (product_details_batch), seller offers or stock (offers_stock), or review text (product_reviews). Fetches the complete product record for one ASIN on one marketplace: title, price, star rating, rating count, images, description, feature bullets, variations and category. Price: $0.003 per call. 404 means the ASIN is absent from that marketplace and IS billed. 503 is a temporary failure on our side and is NOT billed - retry. Bullet points and specs are what Amazon shows for the listing; on multi-variant listings they can describe the product family rather than the exact variant. A null field means Amazon did not show it. Keys of `product_information`, `tech_specs` and the other specification tables are trimmed: Amazon prints some rows twice, once with a trailing space ("Package Dimensions "), and the copies are merged under the clean name; when they differ the listing's own value wins (the second copy of "ASIN" on a variant often names the parent).product_reviewsUse for what customers say about one product. Not for its full review history (Amazon serves full and star-filtered review lists only to signed-in accounts) or for seller feedback (seller_reviews). Returns the overall rating, rating count, review_histogram (percent of all ratings per star), Amazon's 'customers say' AI summary where that marketplace shows one, and the reviews on the product page (typically up to 8 from this marketplace and 5 from other countries), each with rating, review_date, review_country, from_this_marketplace, verified flag and helpful_votes; from_rating/to_rating keep a star window. Price: $0.003 per call. Same 404-billed / 503-not-billed semantics as product_details. No paging or sort: the reviews are those on the product page; review_coverage says how many and from where. from_rating/to_rating filter them. review_histogram (here and on product_details) gives the share of every rating. customers_say is null where Amazon shows no summary (several marketplaces never do); customers_say_note then says so.searchUse to find products by keyword and filters. Rows are result snippets; for the authoritative record of one ASIN call product_details. Search Amazon products by keyword. Filters: page, sort_by, category_id (browse node), min_price / max_price (decimals), product_condition (NEW / USED / RENEWED), brand, seller_id, today_deals and deal_type (coupons, all_discounts, buy_more_save_more). Every answer carries filters_applied, filters_ignored (with the reason) and available_filters for that marketplace. Price: $0.003 per call. Blank values and the literal string 'null' are treated as unset. Invalid page, sort_by, price, product_condition or deal_type is a free 400 naming the parameter and the allowed values. Condition and deal refinements are per marketplace; a marketplace that lacks one gets the unfiltered feed plus an entry under filters_ignored, never a silent empty page. `product_num_ratings` is an integer; `offers_count` is the "N offers" count a result card shows, an integer, and null when the card shows none (most cards; it used to default to 1); `product_brand` is the brand line Amazon prints above some titles (fashion and many branded listings) and null on cards without one -- product_details has `brand_name` for every ASIN; `product_star_rating`, `product_price` and `product_original_price` are decimal strings; a null field means Amazon did not show it. `is_prime` is true when the result carries a Prime badge or its delivery line offers Prime delivery. `metadata.reachable_pages` says how far `page` can go: Amazon serves at most 7 pages of a query even when `metadata.total_pages` counts more (then `pagination_note` says how to split the query). `_links.next` is the next page while there is one; a page past the end is a free 400 `page_out_of_range`. A full page is up to 48 results and about 54 KB; the tool returns the first 10 as light rows by default and the answer carries `_truncated`, `_omitted_fields`, `_projection` and `_notes`. filters_applied echoes the effective sort_by (RELEVANCE when none was sent). A BEST_SELLERS ordering is Amazon's query-scoped popularity, not a category rank: a row's `badges` / `is_best_seller` are what the result card showed for this query, and an ASIN that is #1 in its subcategory can carry no badge here while product_details reports best_seller=true with the rank. For a rank claim, use product_details or best_sellers. An empty `products` list is served as success only when Amazon itself reports 0 results (metadata.total is 0 and `hint` says so). Anything else that is not a usable result is an unbilled, retryable 503 with code upstream_unavailable.product_details_batchUse to enrich a list of ASINs in one call; compare the ASINs in `results` with the ones you sent. Batch variant of product_details. Accepts a comma-separated ASIN list, deduplicates it, and fetches all of them concurrently. Far cheaper and faster than N single calls. Price: $0.0024 per item (max 20). Billed per ASIN processed, including ones that come back not-found. More than 20 ASINs returns 413. Bullet points and specs are what Amazon shows for the listing; on multi-variant listings they can describe the product family rather than the exact variant. A null field means Amazon did not show it. ASINs Amazon has no record for on that marketplace are listed in not_returned (billed, like a not-found product_details call; retrying will not help). The batch record comes from Amazon's app, not the product page: price, rating, availability, images, bullets and variants, but no best-seller ranks, no category path and no merchant (seller) id. For those call product_details per ASIN. On an API key both cost one request per ASIN, so the batch saves calls and time, not money; keyless (x402) it is also cheaper per item.offers_stockUse to compare sellers' current offers and see who holds the buy box, and, with check_inventory, how many units a buyer can add to the cart now. The stock number is not a sales estimate. Not for the listing's own details (product_details). Returns the current offer list per ASIN (seller, price, condition, buy-box winner) and, optionally, the actual purchasable stock quantity. Price: $0.0045 per item (max 10). Billed per lookup, which is more than one per ASIN when check_inventory is true. offers_count=winner returns only the offer flagged is_buybox_winner (offers_total keeps the full count); it used to scope only the inventory check and return every offer. /scrape is a legacy alias for the same handler. When Amazon will not return the offer list for an ASIN, the result carries source=product_page: the featured (buy-box) offer read from the product page, offers_on_amazon (how many offers Amazon says exist) and a note; other sellers' offers and stock are then not included. With check_inventory, a cart check that cannot read a quantity is retried once on another session; one that still fails says so on the offer, inventory_response {"error": "cart check failed", "code": "cart_check_failed", "retryable": true}, is not billed, and never reads as a quantity of 0. Each offer carries `ships_from` (the "Ships from" name: Amazon for FBA, else the seller), `delivery_message` (the offer's own delivery promise, e.g. "FREE delivery Friday, October 16 on orders shipped by Amazon over $35") and `delivery_message_secondary` (the "Or fastest delivery ..." line), null when the offer shows none. `delivery` is the same value as `ships_from`, kept for existing integrations; it never held delivery information. A row for an ASIN that could not be answered carries `error`, `code`, `http_status`, `billed`, `retryable` and `next_step`, like a top-level error: `upstream_unavailable` (not billed, retry that ASIN), `no_offers` ("No offers found": the offer list holds no offer that can be bought as is -- customizable listings have none; billed like a 404) or `asin_redirected` (Amazon answers the ASIN with another listing's offers; billed like a 404). On agent.apiguru.app the answer also carries `success` and `_links` (self, and `details_url` per row); `billable_requests_count` is there on your own key only.best_sellersUse for what sells best in a department right now. The rank is Amazon's, not a sales figure. Best-seller rankings for a department of one marketplace, 50 per page. Every answer carries the department it resolved to and how (category_resolution: by slug, name or a fragment of a name, with a hint when a fragment such as 'shoes' landed on the whole 'Clothing, Shoes & Jewelry' department, or 'subcategory' when a word such as 'camera' named a subcategory), available_categories (that marketplace's departments with slugs; MCP: with compact=false) and available_subcategories (the children of the node shown, with the ids subcategory_code takes). On amazon.com subcategory_code also takes any browse node id at any depth, or a name resolved under the department ("women's shoes", "mules & clogs"); category.subcategory_path gives the node's full path and category.heading the page's own title line. Price: $0.003 per call. No required parameters - calling it bare returns US appliances page 1. `category` accepts a slug, a display name, one of the older US department names, or a unique fragment; category_resolution.via says which, and a fragment match adds a hint naming the subcategories that carry the word, with ids. On amazon.com the whole browse tree is known: subcategory_code takes any node id or a name at any depth, subcategory_name and subcategory_path are filled without a fetch, and available_subcategories lists the node's real children (empty on a leaf). Other marketplaces name only what their navigation showed. page is capped at 5 (a 400 beyond, not a 500). `rank` is the position within the requested list on this page. Rows are the same for every marketplace; only the department vocabulary differs, and the answer carries it.dealsUse for items currently promoted in Amazon's deals feed. Not for one product's price (product_details); for a brand by name use search with brand= and today_deals=true. Returns the current Amazon deals feed: ASIN, title, deal price, list price, discount, deal badge, start/end time and product links. Filter by department (categories), brand id (brands), rating cut-off, price bounds, minimum discount and Prime program. Every answer carries available_filters (the category and brand ids this marketplace accepts, with names), filters_applied / filters_ignored (what took effect) and next_offset (the next page, null when the feed ends). Price: $0.003 per call. Filters are by id: categories takes a department id or name, brands takes brand ids only; available_filters in every answer lists both with names, and filters_applied / filters_ignored report what Amazon honoured. A page is 30 rows; page with offset=next_offset (null when exhausted); total_count caps at 500. min_price, max_price, min_discount and max_discount are applied to the rows after retrieval, scanning up to 3 feed pages per call, so a page can hold fewer than 30 rows and total_count does not reflect them. An empty answer carries a hint saying why. Deal prices expire: check deal_ends_at. The older price_range and discount_range parameters are still accepted, as buckets (1-5 = under 25 / 25-50 / 50-100 / 100-200 / 200 and up; 1-4 = 10 / 25 / 50 / 70 percent off or more) or as bands such as 25-50 and 70+.seller_profile_batchUse to vet sellers: name, rating and feedback counts as Amazon displays them. Returns the storefront profile for each seller id: business name, rating, feedback counts, address and marketplace presence. Price: $0.0036 per item (max 10). Seller ID validation is all-or-nothing: one malformed id rejects the entire request with 400. Every row in results is an object with `status`: `ok` (the profile), `not_found` (Amazon has no page for that id on this marketplace; billed, like a 404) or `unavailable` (could not be retrieved right now; NOT billed on the keyed path, `retryable: true`). A row is never null. billable_requests_count counts ok + not_found rows; on the pay-per-call rail the per-item quote is settled up front, so retry `unavailable` ids in a separate call rather than expecting a partial refund. On agent.apiguru.app the answer also carries `success` and `_links.self`; `billable_requests_count` is there on your own key only.seller_productsUse to list one seller's storefront. Products listed by a seller: a storefront search. Takes the same filters as search -- query, page, sort_by, category_id, min_price / max_price, product_condition, brand, today_deals, deal_type -- and answers with filters_applied, filters_ignored and available_filters like search does. Price: $0.003 per call. A malformed seller_id is a free 400, as on seller_profile_batch. metadata.total_pages counts every page of the result (48 rows a page), but Amazon serves at most 7 pages of one query: metadata.reachable_pages is how far page can go, and when it is less, pagination_note says how to see the rest (min_price/max_price bands or category_id). _links.next is the next page while there is one; a page past the end is a free 400 page_out_of_range. Invalid sort_by, price, product_condition or deal_type is a free 400 that lists the allowed values. No single sort order lists a whole storefront: Amazon's relevance order (the default) can count far fewer products than the store holds and repeats products across pages, and other orders include products it leaves out (measured on one store: relevance 321, NEWEST 1,898; on another, relevance and NEWEST shared 90 of 161 products). Page 1 of a storefront without `query` carries `coverage_note` with the recipe: page through sort_by=RELEVANCE and sort_by=NEWEST, split a store larger than 336 products into min_price/max_price bands, dedupe by asin. An empty storefront carries `note`: Amazon reports 0 products for a seller with no listings on that marketplace and for an id that is not a seller alike, so check it with seller_profile_batch (`_links.seller_profile`). Rows have the search row shape: `offers_count` is null unless the card shows a count, and `product_brand` is null on most storefront cards (Amazon prints no brand line there; product_details has `brand_name`).seller_reviewsUse for a seller's customer feedback (service, shipping). Not for product reviews (product_reviews). Returns paginated seller feedback, optionally filtered to a star-rating window. Price: $0.003 per call. from_rating and to_rating are optional; omit both for unfiltered feedback. A page holds 5 reviews and the answer carries current_page and has_next_page; Amazon exposes no total, so page until has_next_page is false (up to page 100).list_capabilitiesList every Apiguru endpoint with its price, required parameters and supported marketplaces, plus your current access mode, cache and session budget. Free: answers locally with no network request and no charge. Call this before paid tools if you need to plan.send_feedbackReport a bug, ask for a field, or say what would make this API more useful. Free: never billed, no API key needed. Prefer GitHub if you have an account -- an issue at https://github.com/apiguru-app/agent-kit/issues gets a reply on the thread, this wall does not. Use this tool when you have no GitHub account or nothing to attach one to. message: what happened or what you want. Be specific: the tool, the parameters, the field, what you expected, what you got, and the request_id from the answer. One issue per entry -- a five-point list cannot be closed point by point. category: bug | wish | praise | question | other endpoint: which tool or path it is about, e.g. "search". agent: what you are, e.g. "acme-pricing-bot/2.1". Optional. contact: a GitHub handle or email if you want a reply. Shown publicly on the wall. Optional.
TrustRails MCP Server tools 2
search_productsHOW TO CALL THIS TOOL — read before every call: Decompose the user's request into filters first. Only what's left over goes in query. STEP 1: brand name → brand filter. STEP 2: product category → category filter. STEP 3: price → min_price/max_price. STEP 4: RAM, storage, screen size, resolution, refresh rate, wattage, Wi-Fi generation → constraints. STEP 5: what remains → query. BAD: query='Sony headphones under £200' | GOOD: brand='Sony', category='Headphones', max_price=200, no query. BAD: query='tablet' | GOOD: category='Tablets', no query. BAD: query='macbook neo' | GOOD: brand='Apple', category='Laptops', query='neo'. BAD: query='Samsung QLED TV' | GOOD: brand='Samsung', category='TVs', query='qled'. If brand+category alone cover what the user wants, omit query entirely. Only put differentiating terms in query: model lines (neo, ultra, oled), variants, model numbers (WH-1000XM5, s25 ultra). Query words must appear in the title, except words naming the category ('router' in Networking) and bare numbers or specs ('4070', '16GB'), which are ignored when finding products and only rank them. Put a model number with its prefix ('RTX 4070', not '4070') and check each title for it. Leave out use-case words like gaming, cheap or best. CROSS-CATEGORY NOTE: Gaming headsets → category='Headphones', query='gaming headset'. The Gaming category is consoles/controllers/accessories only. Always set lite=true (it still carries `attributes`). If 0 results, broaden the query or drop filters (but never present a near miss as meeting a requirement). Searches 26,000+ UK electronics products across 7 retailers with price comparison. Prices are in GBP. Every listing is new (refurbished and used are excluded). PRICE COMPARISON: for a final pick with offer_count > 1, get_product returns offers[] (sorted in-stock first, then cheapest): show the cheapest in-stock retailer, the other prices with the difference and the exact saving among in-stock offers. Before claiming a saving, read offers[].title (from get_product): they must name the same model; if they differ, don't claim one. Before recommending any pick, check its title is the product type asked for (not a cable, accessory or adapter). COMPARING SPECS: compare products from the `attributes` in the search results, not by calling get_product on each. Every spec known for a product is there as {status, value}, or {status, values} when conflicting, without sources; names and units are as in `constraints`. 'confirmed' (two or more retailers state the same value) and 'inferred' (one retailer's title states it) are both the product's spec: state the value. Only `conflicting` (retailers disagree: say so, don't pick one) or a missing name (unknown) needs a caveat. A product with no `attributes` has none of these seven specs known: say so only if the user asked about one. Call get_product only for your final 1-3 picks, and only when you need what search lacks: what only the retailer's description has (processor, GPU, ports, weight, battery), or every retailer's offer and buy link (search results carry only the best offer's purchase_url (cheapest in stock)). A pick with offer_count 1 needs no call unless the user asked for a description-only detail. Don't guess those details from titles. SPEC REQUIREMENTS: put exact requirements in `constraints`, not in query, and always set `category` (and brand if known) with `constraints`: a search of only specs is rejected. If a requirement is ambiguous (e.g. '16GB' could be RAM or storage), ask the user or search without that constraint. With constraints, every product has `constraint_status` per name: 'matched' = a retailer's title states a value that meets it. 'unverified' = not known to meet it: check `attributes[name]`, where `conflicting` means retailers disagree and missing means unknown. Never treat 'unverified' as a match or say a product meets a requirement because it was returned: tell the user it is unconfirmed. Products whose stated value fails are left out (`excluded_by_constraints`). Matched results come first, also with sort='price_asc'. With constraints, `total` counts the products that match every constraint and `unverified_total` the unverified products that passed the other filters (only some may be in `products`). If `total` is 0, say no product is known to meet every requirement and offer the unverified ones only as unconfirmed. If `candidates_truncated` is true, the first 2,000 candidates in the chosen sort order were checked and more exist: add a brand or category, or a narrower query, and search again before saying nothing matches. If the search was already narrowed, tell the user the results may be incomplete. STOCK: availability is in_stock, low_stock, out_of_stock or unknown (the retailer gave no stock signal: say so, don't assume). When availability is out_of_stock, mention it as an alternative and suggest checking back — do not silently omit it. purchase_url is a trustrails.app/go/ redirect through an affiliate link; TrustRails may earn a commission, and the price is the same. Colour variants have separate barcodes and are separate products: when price matters, search again without the colour or check other colours of the same model.get_productGet full details for a single product by ID. Returns `attributes`: structured specs read from retailer titles, each name mapping to {status, value, sources}; a conflicting one has values: [{value, sources}] instead of value and sources. Names and units as in the search constraints argument. status: 'confirmed' = two or more retailers state the same value; 'inferred' = one retailer's title states it; 'conflicting' = retailers state different values (none is picked, tell the user they disagree; a retailer can appear under two values, so read offers[].title to see which listing states which); a missing name = unknown. Also returns specs.description, the retailer's own prose: use it only for details attributes do not cover (processor, GPU, ports, weight, battery, features); if it doesn't give a detail, tell the user it isn't listed. It can describe another configuration or a maximum ('up to 32GB'), so it never overrides or fills in an attribute: if an attribute is missing or conflicting, that spec is unknown or unconfirmed, and you may mention what the description says only as 'the retailer's description mentions X, unconfirmed'. It also returns pricing, availability, delivery time, and all retailer offers with per-retailer pricing (offers[].stock is a unit count only when the retailer supplies one, otherwise null). Accepts both canonical product IDs and original retailer offer IDs. Use this after search_products only for your final 1-3 picks, and only when you need what search lacks: details only the description has, or every retailer's offer and buy link. Search results already carry `attributes` to compare specs.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Apiguru Amazon Data
{
"mcpServers": {
"apiguru-amazon-data": {
"command": "npx",
"args": [
"-y",
"apiguru-mcp"
]
}
}
}
TrustRails MCP Server
{
"mcpServers": {
"server-3": {
"command": "npx",
"args": [
"-y",
"@trustrails/mcp-server"
],
"env": {
"TRUSTRAILS_API_KEY": "YOUR_TRUSTRAILS_API_KEY_HERE"
}
}
}
}
Frequently asked questions
Apiguru Amazon Data is categorized under E-Commerce and uses a local stdio subprocess. TrustRails MCP Server belongs to E-Commerce and uses a local stdio subprocess. Pick Apiguru Amazon Data for e-commerce work and TrustRails MCP Server for e-commerce.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Apiguru Amazon Data is listed as freemium — a free tier with paid plans. Auth: no auth required. TrustRails MCP Server has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add apiguru-amazon-data and server-3 as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Apiguru Amazon Data has a quality signal of 64/100 (Good) with 2 views, 0 installs and 0 GitHub stars. TrustRails MCP Server has 55/100 (Good) with 2 views, 0 installs and 0 GitHub stars.