Easyparser — Amazon Product & Seller Data

get_seller_products

Read-only

Extract a seller's full product catalog: every ASIN they sell with brand, category, price, Prime status, variant counts, and rating data. Also returns dynamic refinement filters (department, shipping, sustainability) for drilling into the catalog.

Use this tool for competitor inventory analysis, stock monitoring, and pricing-strategy research. If you need the seller's legal identity or reputation instead of their products, use get_seller_profile.

Each page costs 1 credit. Start with one page and use sort_by (e.g. 'exact-aware-popularity-rank' for best sellers first) to surface the most relevant products early. Provide EITHER seller_id OR url — never both.

Input Schema

Name	Required	Description	Default
`url`	No	Full Amazon seller profile or storefront URL (e.g. https://www.amazon.com/sp?seller=A1MCYUGJD2ILFU).
`domain`	No	Amazon marketplace domain extension. Determines the regional Amazon site the data is fetched from. Use the domain that matches the user's market — prices, availability and rankings differ across marketplaces.	.com
`sort_by`	No	Catalog ordering. 'featured-rank' is default; 'exact-aware-popularity-rank' sorts by popularity (best sellers first); 'price-asc-rank'/'price-desc-rank' by price; 'date-desc-rank' by newest.
`language`	No	Language code for the Amazon page, in locale format (e.g. en_US, de_DE, tr_TR). Affects the language of titles, descriptions and reviews in the response.
`max_page`	No	Ending page number. Each page costs 1 credit; max 5 pages per request. Default 1.
`min_page`	No	Starting page number. Default 1.
`seller_id`	No	Amazon's unique seller identifier (e.g. A1MCYUGJD2ILFU). Found in seller profile URLs as the 'seller=' or 'me=' parameter.
`exclude_refinements`	No	If true, omits the refinement filter list from the response, reducing payload size. Default false.

Output Schema

Name	Required	Description
`data`	No	Parsed Amazon data for the operation.
`success`	Yes	True when the request completed.
`operation`	Yes	Easyparser operation that ran, e.g. DETAIL or OFFER.
`request_id`	No	Easyparser request ID, useful for support and error logs.
`credits_used`	No	Credits charged for this request.
`credits_remaining`	No	Credits left on the account after this request.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 11, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "credits_remaining": {
+      "description": "Credits left on the account after this request.",
+      "type": "number"
+    },
+    "credits_used": {
+      "description": "Credits charged for this request.",
+      "type": "number"
+    },
+    "data": {
+      "description": "Parsed Amazon data for the operation."
+    },
+    "operation": {
+      "description": "Easyparser operation that ran, e.g. DETAIL or OFFER.",
+      "type": "string"
+    },
+    "request_id": {
+      "description": "Easyparser request ID, useful for support and error logs.",
+      "type": "string"
+    },
+    "success": {
+      "description": "True when the request completed.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "success",
+    "operation"
+  ],
+  "type": "object"
+}

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, non-destructive, openWorld), and the description adds real operational context the annotations lack: per-page credit cost, a 5-page cap, and the payload-reducing effect of exclude_refinements. It stops short of describing response structure or failure modes, so it is strong but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight paragraphs: catalog contents first, then usage and routing, then cost/sort/exclusivity mechanics. Every sentence carries actionable information and the most decision-relevant facts are front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and the description correctly limits itself to what the structured fields do not cover: cost per page, pagination cap, sort semantics, and input exclusivity. Nothing needed to invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already carries the parameter definitions (baseline 3). The description goes beyond it by supplying a concrete sort_by value with its effect ('exact-aware-popularity-rank' for best sellers first) and by stating the seller_id/url exclusivity constraint that the schema itself does not encode.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Extract a seller's full product catalog') and enumerates the returned fields (ASIN, brand, category, price, Prime status, variant counts, rating data). It explicitly names the sibling it is not — get_seller_profile — so an agent can route without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names three concrete use cases (competitor inventory analysis, stock monitoring, pricing-strategy research) and an explicit exclusion with the alternative: 'If you need the seller's legal identity or reputation instead of their products, use get_seller_profile.' It also gives the mutual-exclusion rule 'Provide EITHER seller_id OR url — never both.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Easyparser — Amazon Product & Seller Data tools Inspect

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