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Glama

Easyparser — Amazon Product & Seller Data

by com.easyparser

lookup_product

Read-only

Convert an external product identifier (UPC, EAN, GTIN, ISBN, JAN, MINSAN) into the corresponding Amazon ASIN, with an essential product snapshot. This is the bridge between manufacturer/retail barcodes and the Amazon ecosystem.

Use this tool when the user has a barcode or standard product code and wants to find the matching Amazon listing. Typical workflows: catalog matching, inventory synchronization, converting supplier data into Amazon ASINs. Also accepts ASIN as input type if you need to validate one.

You MUST set identifier_type to match the code you have — guessing the wrong type returns no results. UPC is 12 digits, EAN/GTIN is 13, ISBN is 10 or 13 (books). If the user gives a keyword instead of a code, use search_products instead. Costs 1 credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoAmazon 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
identifierYesThe product code value (e.g. '724382975021' for a UPC). Digits only for barcode types.
identifier_typeYesThe type of code provided. UPC: 12-digit US barcode. EAN/GTIN: 13-digit international barcode. ISBN: book identifier. JAN: Japanese barcode. MINSAN: Italian pharma code. ASIN: Amazon's own identifier.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare the operation read-only and non-destructive; the description adds non-obvious behavioral facts: wrong identifier_type matches return nothing, and each call costs 1 credit. It doesn't describe response details beyond 'essential product snapshot', but the annotations lower the burden.

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?

Front-loaded with the core purpose, followed by when-to-use, parameter rules, and the sibling alternative. Every sentence adds actionable information without padding.

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?

For a conversion tool with no output schema, it explains the output (ASIN plus product snapshot), the key failure mode, cost, marketplace domain handling via schema, and the correct alternative for keywords. This is enough for an agent to select and invoke it 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?

The schema covers all 3 parameters, and the description adds valuable semantic detail beyond it: UPC is 12 digits, EAN/GTIN 13, ISBN 10/13, and matching identifier_type is mandatory. This extra guidance helps the agent construct correct calls.

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?

The description states a specific conversion task — external product identifiers (UPC, EAN, GTIN, ISBN, JAN, MINSAN) to Amazon ASIN — and clearly distinguishes itself from sibling search_products by saying keywords should go there. It also notes ASIN validation as a secondary use, which further clarifies scope.

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?

It gives explicit when-to-use guidance ('Use this tool when the user has a barcode or standard product code'), describes typical workflows, and names the alternative for non-code inputs ('use search_products instead'). This is unambiguous routing.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct resource or action, and overlapping data is carefully disambiguated in the descriptions—e.g., get_product_detail includes BSR and dimensions, but get_bestseller_rank and get_package_dimensions are explicitly positioned as narrower alternatives. The bulk-job tools also form a clear pipeline with no realistic confusion between listing jobs, inspecting items, fetching item data, and checking webhook logs.

Naming Consistency4/5

The dominant get_* pattern is consistent for data retrieval, and list_* is used for collection-style endpoints. Minor deviations like check_credits, lookup_product, and search_products are understandable but break the strict verb_noun consistency enough to prevent a perfect score.

Tool Count4/5

At 17 tools, the server is slightly above the ideal 3-15 range, but the count is justified by the breadth of the domain: product details, offers, sales history, seller intelligence, bulk job monitoring, account credits, and error logs. Each tool earns its place, and the heavier count does not feel bloated.

Completeness4/5

Real-time product and seller data coverage is strong, including search, barcode lookup, product detail, offers, BSR, dimensions, sales history, seller profile, seller products, and seller feedback. The main gap is that bulk jobs can be listed and inspected but there is no tool to create or submit a new bulk job from the MCP server, leaving that workflow incomplete.

Resources