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SEO and Keyword Data API

by com.duoleads.keywords
OverviewDiscussionsAdmin

Amazon keyword ideas and volume

amazon_keywords
Read-onlyIdempotent

Amazon keyword ideas for a seed: average monthly Amazon searches of the seed and of up to 100 related Amazon searches, each with its distance from the seed and the searches Amazon relates to it, US (or SA, AE, EG) market, from Amazon data, $0.04 a call. Use when researching product listing keywords or Amazon demand. A seed with no data is an empty answer, which is still charged. Bad input is a free 400; a data source failure is not charged. Price: $0.04 per successful call, paid over x402 (USDC on Base); pass the payment in _meta["x402/payment"].

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": {
      "keyword": "<keyword>"
    },
    "name": "amazon_keywords"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoRows to return, 1-100. Default 20.
keywordYesSeed keyword (at most 80 characters).
locationCodeNoAmazon market: 2682, 2784, 2818, 2840 (2840 = United States, 2682 Saudi Arabia, 2784 United Arab Emirates, 2818 Egypt). Default 2840.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent/openWorld annotations: it discloses that an empty result is still charged, that a bad input yields a free 400, that a data source failure is not charged, and that payment goes via x402 (USDC on Base) in _meta["x402/payment"]. That is exactly the cost and payment behavior an agent needs before calling a paid tool.

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?

Front-loaded with the core output shape before usage and billing details, and nearly every clause carries information. The price is stated twice ("$0.04 a call" mid-text and again as "Price: $0.04 per successful call" at the end), a small redundancy in an otherwise dense description.

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?

There is no output schema, so the description carries the return-value burden and does so by naming each result field, the markets, and the data source. Combined with the billing and failure-mode disclosure, an agent has everything needed to decide and invoke 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?

With 100% schema coverage the schema already defines keyword, limit, and locationCode, but the description adds that the seed yields 'up to 100 related searches' and spells out the market set as US (or SA, AE, EG), reinforcing the locationCode semantics. Minor added value over an already-complete schema.

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?

Names a specific verb+resource (Amazon keyword ideas for a seed), enumerates the return fields (average monthly searches, up to 100 related searches, distance from seed, related terms), and scopes it to Amazon data and markets. The 'Amazon' qualifier cleanly separates it from generic siblings like keyword_ideas and related_keywords.

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?

"Use when researching product listing keywords or Amazon demand" gives a clear usage context that routes the agent to this tool for Amazon-specific demand research. It does not name alternatives (e.g., keyword_ideas or amazon_search) or state exclusions, so it falls just short of the top score.

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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