Skip to main content
Glama
vantagemcp

vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

find_citation_leaders

Read-onlyIdempotent

Find which domains dominate AI-answer citations for a keyword, and check whether a competitor domain outranks yours.

Instructions

Find which domains dominate AI-answer citations for a topic/keyword, and optionally check whether a specific domain shows up among them. Use this to answer 'who's winning AI search for this topic' or 'is my competitor cited more than me for X'.

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: {"keyword", "platform", "top_domains" (list of {"domain", "mentions"}, most-cited domains for this keyword/platform, order as ranked by the provider), "top_domains_limit" (int, the provider's own cap on this list - absence from it is NOT evidence a domain has zero citations, only that it did not rank in the top top_domains_limit), "compare_domain_rank" (int|null, only present when compare_domain was passed: the domain's 1-based position in top_domains, or null if it did not rank in the top top_domains_limit), "country", "language", "source_mix" ({"community_pct" (share of these mentions that go to community sites such as Reddit, YouTube, X, Quora), "community_domains", "other_domains"}: a high community_pct means this topic is won by what people say about a brand elsewhere, not by any one site's pages)}.

This tool's citation universe is the provider's tracked mention corpus for the keyword, which is a different measurement from analyze_citation_structure's single live answer - the two can legitimately disagree on whether a given domain shows up.

Use check_prompt_coverage instead if you already know which domain you care about and just want to know whether it is cited.

Args: keyword: the topic/query to check, e.g. "best project management tool". platform: "chat_gpt" or "google" (Google's AI Overview). Defaults to chat_gpt. Perplexity and Gemini aren't available - the underlying data provider doesn't cover them for this check. compare_domain: optional bare domain to look up in the results (exact match against the registrable domain, e.g. "notion.so" will not match "mynotion.so.example.com"). country: market to check, e.g. "Italy". Defaults to "United States". chat_gpt only has data for the United States; use platform "google" for any other country. language: language code, e.g. "it". Defaults to "en" (the only option for chat_gpt).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoUnited States
keywordYes
languageNoen
platformNochat_gpt
compare_domainNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.7.0
    • addedInput schema / properties / country
      Added value: +{
+  "default": "United States",
+  "title": "Country",
+  "type": "string"
+}
    • addedInput schema / properties / language
      Added value: +{
+  "default": "en",
+  "title": "Language",
+  "type": "string"
+}
  2. Addedv1.5.2

TDQS

A5/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, open-world behavior, and the description adds substantial extra context: exact quota cost (10 units/call), the caveat that absence from top_domains is not evidence of zero citations, and the source_mix interpretation. It also clarifies how this tool's citation universe differs from analyze_citation_structure.

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?

The description is long but every section earns its place: purpose, typical user questions, quota, return semantics, caveats, sibling differentiation, and per-parameter guidance are all front-loaded in a logical order. Nothing is redundant or filler.

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?

Given 5 parameters, no output schema, and no enums, this description is unusually complete: it explains every parameter, the return shape, open-world absence semantics, quota costs, platform/country/language restrictions, and when to prefer a sibling tool. An agent has everything needed to call it correctly.

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 it succeeds: keyword usage, platform options with unavailable providers, compare_domain exact-match semantics with a concrete example, country restrictions tied to platform, and language defaults are all documented. This meaningfully exceeds the bare 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?

The description states a specific verb and resource: find which domains dominate AI-answer citations for a topic/keyword, with an optional domain comparison. It clearly differentiates this from siblings by naming analyze_citation_structure and check_prompt_coverage and explaining measurement differences.

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?

It gives explicit use cases ('who's winning AI search for this topic' or competitor comparison), names the alternative check_prompt_coverage for when a domain is already known, and notes platform/country/language limitations. This leaves no ambiguity about when to invoke this tool.

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