highbrow_fame data APIs (pay per call)

AI search visibility: is a brand cited by ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews

ai_visibility_check

Read-only

Asks up to five AI engines (ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews) one question with live web search and reports, per engine, whether a brand's website is cited, at which position, which competitors are cited instead, and the sources, plus a 0-100 visibility score. Suited to AI search visibility (GEO, AEO) checks and brand monitoring. $0.05 per engine asked; the engines parameter selects them, all five when omitted ($0.25).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ai_visibility_check"
  }
}

Input Schema

Name	Required	Description
`brand`	No	Your website domain, e.g. "hubspot.com" (a full link is reduced to the domain). The brand counts as cited when an engine lists a page of this site among its sources or names the brand in its answer.
`query`	No	The question as people ask an AI assistant, 3 to 300 characters, e.g. "best CRM for small business". One question per request.
`answer`	No	true (default): include each engine's full answer text. false: a smaller response without it.
`country`	No	2-letter country code for Google AI Overviews (default us), e.g. gb, ca, au.
`engines`	No	Engines to ask, separated by commas: chatgpt, perplexity, claude, gemini, google-ai-overviews. Default: all five (google-ai-overviews only with language en). Fewer engines answer faster.
`language`	No	Language of the question and the answers (default en).
`competitors`	No	Up to 5 competitor domains separated by commas, e.g. "salesforce.com,pipedrive.com". Each gets the same checks and a place on the leaderboard.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With readOnlyHint and openWorldHint already covering the safety and external-call profile, the description still adds real context: it costs $0.05 per engine ($0.25 for all five), it performs live web searches, one question per request, and fewer engines respond faster. The one caveat is api-credit pricing and speed, but retry/timeout/latency behavior is not disclosed, so it is not quite a 5.

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?

Three dense sentences, front-loaded with the action, then the output shape, then use case and cost. Every sentence carries information, though the pricing/engine-selection sentence packs two ideas that could be split for scannability.

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 convey the return shape — it does: per-engine citation, position, competitors cited instead, sources, and a 0-100 score. With the cost, engine-selection, and language/Google-AIO constraint noted, an agent has what it needs to call this 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 the baseline is 3. The description goes beyond the schema by tying the engines parameter to cost ($0.05 each, $0.25 total) and by explaining the citation criterion (page on the site among sources, or brand named in the answer). It does not resolve which parameter controls what in the answer, but the schema already does.

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 names a specific action (ask up to five named AI engines one question with live web search) and a specific payload returned per engine: citation status, position, competing brands cited, sources, plus a 0-100 visibility score. That is concrete enough to separate it from every sibling (classifieds/grocery/jobs/property search), which are unrelated.

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 states the intended use explicitly: 'Suited to AI search visibility (GEO, AEO) checks and brand monitoring.' It also gives a selection rule for engines (all five when omitted, fewer answer faster). What's missing is when NOT to use it, but no sibling is a plausible alternative here, so the gap is small.

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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