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Amazon Seller MCP Server — AgentXray

by ai.agentxray
OverviewDiscussionsAdmin

One product over time

get_sku_trend
Read-onlyIdempotent

One SKU over time on one marketplace: units per day, the price buyers actually paid after promotions against the listed price, sessions, conversion and Buy Box %, and settled net profit per week. Use it for 'how is this product doing over time', 'did my price change hurt conversion', 'what do buyers really pay'.

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": {
      "sku": "<sku>"
    },
    "name": "get_sku_trend"
  }
}

Input Schema

NameRequiredDescriptionDefault
skuYesThe seller SKU.
daysNoWindow in store days, 7-365 (default 90).
accountNoSeller id of the client account (agencies with several accounts on this marketplace).
end_dateNoCustom range end, YYYY-MM-DD (inclusive).
start_dateNoCustom range start, YYYY-MM-DD (inclusive).
marketplace_idNoMarketplace (inferred when only one is connected).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior and a closed-world scope. Beyond that, the description adds useful behavioral context by defining the price metric as post-promotion versus listed price and by specifying that net profit is settled on a weekly cadence.

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?

Two tightly written sentences with no filler. The metric scope is front-loaded, and the example use cases follow naturally without repeating structured details.

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

Completeness4/5

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

With no output schema, the description carries the burden of explaining return values and does so by naming the core metrics and their aggregation cadence. It stops short of describing output structure or edge cases, but is otherwise sufficient for an agent to call the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so all six parameters are already documented in the input schema. The description does not add syntax or usage constraints beyond what the schema provides, making the baseline 3 appropriate.

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

Purpose4/5

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

The description clearly states the resource ('one SKU over time on one marketplace') and the specific metrics returned, including units, price paid, sessions, conversion, Buy Box %, and settled net profit. It distinguishes itself from snapshot-style siblings by emphasizing trend over time, but it does not explicitly name an alternative tool for comparison.

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

Usage Guidelines4/5

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

It gives explicit use cases such as 'how is this product doing over time,' 'did my price change hurt conversion,' and 'what do buyers really pay.' However, it does not state when not to use the tool or name alternative siblings for different needs.

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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