Easyparser — Amazon Product & Seller Data

get_similar_products

Read-only

Find products Amazon considers similar to a given ASIN: returns the source product plus a 'similar' list of related ASINs with title, brand, category and image. This is the competitor and alternative discovery tool.

Use this tool when the user asks for alternatives, competing products, or 'what else is like this?' for a specific ASIN. For keyword-based discovery without a starting product, use search_products instead. To compare the found products in depth, follow up with get_product_detail on the ASINs that matter.

Cost depends on similar_limit: 10 results = 1 credit (default), 50 = 6 credits, 100 = 11 credits. If no similar products are found, only 1 credit is charged. Keep the default 10 unless the user asks for a broad list. Delivery-address localization is not supported for this operation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "asin": "<asin>"
    },
    "name": "get_similar_products"
  }
}

Input Schema

Name	Required	Description	Default
`asin`	Yes	Amazon Standard Identification Number, a 10-character alphanumeric product identifier (e.g. B0CJB6V2L5). Found in the product URL after /dp/ or /gp/product/.
`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, because prices, availability and rankings differ across marketplaces.	.com
`similar_limit`	No	Maximum number of similar products to return: '10' (1 credit, default), '50' (6 credits) or '100' (11 credits).	10

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.

Changed2 schema fields changedNov 6, 2026

changedInput schema / properties / asin / description

Previous value: -"Amazon Standard Identification Number — a 10-character alphanumeric product identifier (e.g. B0CJB6V2L5). Found in the product URL after /dp/ or /gp/product/."New value: +"Amazon Standard Identification Number, a 10-character alphanumeric product identifier (e.g. B0CJB6V2L5). Found in the product URL after /dp/ or /gp/product/."

changedInput schema / properties / domain / description

Previous value: -"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."New value: +"Amazon marketplace domain extension. Determines the regional Amazon site the data is fetched from. Use the domain that matches the user's market, because prices, availability and rankings differ across marketplaces."

AddedNov 6, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only cover safety (readOnly, openWorld, non-destructive), and the description adds economics the agent cannot get elsewhere: a concrete credit table per similar_limit, the special rule that zero results still cost 1 credit, and an explicit recommendation to keep the default 10. It also discloses a real operational constraint — delivery-address localization is not supported — which affects how the agent should set user expectations.

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

Conciseness4/5

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

Well organized and front-loaded: purpose, when-to-use, alternatives, then cost. Some redundancy with the schema in the credit breakdown (the same three credit figures appear in the similar_limit enum description), so a sentence could be trimmed, but nothing is wasted or buried.

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?

An output schema exists so return values need only be sketched, and the description does exactly that. With safety in annotations, cost and limits disclosed, sibling routing given, and a known non-supported feature called out, an agent has everything needed to select and invoke this tool correctly.

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 coverage is 100%, so all three parameters are already documented, and the description's cost table largely restates the similar_limit enum. It does add genuine decision guidance beyond the schema ('keep the default 10 unless the user asks for a broad list') and ties domain choice to marketplace differences implicitly, though it adds nothing about the asin format itself.

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 ('Find products Amazon considers similar to a given ASIN') and immediately specifies the return shape: source product plus a 'similar' list with title, brand, category, image. It also self-labels as 'the competitor and alternative discovery tool', which separates it from lookup_product and search_products.

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?

Explicit when-to-use ('user asks for alternatives, competing products, or what else is like this?') plus a named exclusion routing to search_products for keyword discovery without a starting ASIN. It also prescribes a follow-up path via get_product_detail for deeper comparison, so the agent knows both boundaries and next steps.

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

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