Skip to main content
Glama
vantagemcp

vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Find questions AI cites your site for

find_cited_questions
Read-onlyIdempotent

Discover which questions AI answer engines already cite a domain for, ranked by volume. Use it to identify existing citations without guessing keywords.

Instructions

Find the questions people ask AI answer engines where a domain is already cited as a source, most-asked first. Starts from the domain, so nobody has to guess keywords first. Use this to answer 'what does ChatGPT already cite us for' or to pick the keywords to feed check_prompt_coverage and analyze_citation_gap.

Read-only: no side effects, safe to retry. Costs 10 quota units/call (free tier is 30 units/month shared across every metered tool, so up to 3 calls to this tool alone if nothing else is used that period).

Returns: {"domain", "platform", "country", "language", "total_questions" (int, every tracked question citing the domain, which can exceed the list), "questions" (up to limit, most-asked first: {"question", "ai_search_volume" (monthly asks as the provider estimates them), "your_position" (1-based position of the domain among that answer's sources), "source_domains" (who else that answer cites), "last_seen" (when the provider last recorded this answer, UTC)})}. An empty list means the provider's tracked answers do not cite the domain, not that no answer anywhere does.

This reads the provider's tracked answer corpus, the same measurement as find_citation_leaders, not a live answer: re-check a question with check_prompt_coverage to see today's answer.

Args: domain: bare domain, e.g. "example.com" (no https://, no www). Subdomains are included. platform: "chat_gpt" (default) or "google" (Google's AI Overview). limit: how many questions to return, 1 to 20. Default 20. country: market, e.g. "Italy". Defaults to "United States". chat_gpt only has United States data; use platform "google" elsewhere. language: language code, e.g. "it". Defaults to "en", the only option for chat_gpt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
domainYes
countryNoUnited States
languageNoen
platformNochat_gpt

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.8.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds context annotations cannot carry: quota cost (10 units/call, 30 unit free tier shared across metered tools) and the important semantic caveat that an empty list means the provider's tracked corpus lacks the domain, not that no answer anywhere cites it.

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?

Purpose, cost, return shape, and parameter notes are ordered logically and mostly front-loaded. The inline return-value block is long but earns its place given there is no output schema; a couple of parenthetical explanations could be trimmed.

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?

With no output schema, the description fully specifies the return object, field meanings, truncation behavior (total_questions can exceed the returned list), and the key limitation of the data source. Nothing needed to call or interpret the tool is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden and does so: bare domain format with subdomains included, platform values with default, limit range (1-20, default 20), country default plus the chat_gpt-only-United-States constraint, and language default plus the en-only constraint for chat_gpt.

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?

States a specific verb+resource with scope: 'Find the questions people ask AI answer engines where a domain is already cited as a source, most-asked first.' It also differentiates itself from siblings by naming find_citation_leaders (same measurement corpus) and check_prompt_coverage/analyze_citation_gap as downstream consumers.

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?

Explicitly gives the use case ('what does ChatGPT already cite us for') and the follow-on workflow ('pick the keywords to feed check_prompt_coverage and analyze_citation_gap'). It also states when to re-verify with check_prompt_coverage instead of trusting this corpus snapshot.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools