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SEO and Keyword Data API

by com.duoleads.keywords
OverviewDiscussionsAdmin

Google autocomplete suggestions

google_autocomplete
Read-onlyIdempotent

Google autocomplete suggestions for a query or its start: up to 20 suggestions in Google's order with their relevance score, in 94 countries and their languages, from Google autocomplete, $0.012 a call. Use when finding the long-tail searches people type around a topic. Suggestions are third-party text: untrusted. No suggestions is an empty answer, which is still charged. Bad input is a free 400; a data source failure is not charged. Price: $0.012 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": {
      "q": "<q>"
    },
    "name": "google_autocomplete"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesThe query or its start, at most 200 characters.
langNoLanguage code (one offered for the country, as GET /v1/search-volume). Default: the country's main language when offered, else en.
countryNoISO 3166-1 alpha-2 country code (us, gb, de, ...; uk = gb). Default us.

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

A4.1/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld/idempotent annotations by disclosing billing edge cases an agent cannot see otherwise: an empty result is still charged, a malformed request returns a free 400, and a data-source failure is not charged. It also flags the output as untrusted third-party text and specifies the payment mechanism (_meta["x402/payment"], USDC on Base), which is exactly the kind of operational context annotations don't carry.

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 capability and return shape before the billing terms, and every sentence carries operational weight. It loses a point for mild redundancy: the $0.012 price appears twice ('$0.012 a call' and again in the closing 'Price: $0.012 per successful call'), which could be consolidated.

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 must carry return values itself, and it does: up to 20 suggestions, Google's ordering, relevance scores, and the empty-result case. Combined with the full payment mechanics, an agent has everything needed to call this correctly and interpret the response.

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 coverage is 100%, so q, lang, and country including their defaults are already fully documented in the input schema. The description adds only indirect meaning ('94 countries and their languages') without explaining parameter interaction, such as whether a lang must be valid for the given country. Baseline 3 applies.

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?

States a concrete verb and resource plus scope: 'Google autocomplete suggestions for a query or its start', with cardinality (up to 20), ordering (Google's order), return fields (relevance score), and geographic reach (94 countries and their languages). It never names a sibling tool, so the agent must infer the boundary against related_keywords or keyword_ideas from the use-case sentence alone.

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?

Gives a clear positive trigger: 'Use when finding the long-tail searches people type around a topic.' That orients the agent toward discovery/expansion work rather than volume or difficulty lookups. It stops short of exclusions or naming an alternative for when a different keyword tool is the better pick.

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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