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vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Compare your page with the cited answer

analyze_citation_gap
Read-onlyIdempotent

Compare your page's structure to the AI-cited answer for a keyword and get an ordered rewrite brief showing exactly what to change to earn citations.

Instructions

Compare your own page's structure against the AI-generated answer actually cited for this keyword, and return a fix brief: ordered rewrite instructions for your page, not just a description of the winner. Use this to answer 'what should I change on this page to get cited' rather than only 'what does a winning answer look like'. Carry out the fix_brief on the user's page in their own words; it never contains the cited answer's text.

Read-only: no side effects, safe to retry. Costs 1 quota unit/call (free tier is 30 units/month shared across every metered tool, so up to 30 calls to this tool alone if nothing else is used that period).

Returns: {"keyword", "your_url", "winning" (structure of the AI-cited answer, same shape as analyze_citation_structure), "yours" (same structure computed for your_url, including its own "outline" and "has_table", with "num_links_out"/"linked_domains" standing in for source count), "gaps" (list of plain-English differences worth acting on), "possibly_missing" (heads from the winning outline whose key words mostly do not appear on your page; word matching, so check each before adding it), "fix_brief" (list of instructions, most important first: opening, number, list, sections, missing points, table, sources, then a reminder to write in your own words - or a "no structural change indicated" line when every check already matches - and always last, one off-site step drawn from the winning answer's source_mix: which community sites (Reddit, YouTube, X...) it cites, or which other sites to get mentioned on. Page shape gets a page into the running; being cited is decided mostly by what other sites say about the brand)}, or {"error"} if either side couldn't be fetched/parsed.

Use analyze_citation_structure instead if you just want the winning answer's shape, not a comparison against your own page. Use check_prompt_coverage first if you have several keywords and do not yet know which ones you are missing from - this tool is for one keyword you already know needs work.

Args: keyword: the topic/query to check, e.g. "best project management tool". your_url: full URL of your own page to compare, e.g. "https://example.com/best-project-management-tools". country: market to read the cited answer in, e.g. "Italy". Defaults to "United States". language: language code, e.g. "it". Defaults to "en". engine: "chat_gpt" (default), "gemini" or "perplexity": whose answer to compare your page against.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
engineNochat_gpt
countryNoUnited States
keywordYes
languageNoen
your_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.8.0
    • addedInput schema / properties / engine
      Added value: +{
+  "default": "chat_gpt",
+  "title": "Engine",
+  "type": "string"
+}
  2. 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"
+}
  3. Addedv1.5.2

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses cost (1 quota unit/call, 30/month shared free tier), confirms retry safety and no side effects, and adds a critical behavioral constraint that the fix_brief never contains the cited answer's text and must be rewritten in the user's own words. It also enumerates the return payload and the error case, which no structured field provides.

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 and cost are front-loaded, and the dense returns block earns its space given there is no output schema. It is longer than ideal and the fix_brief field enumeration could be tightened, but almost every clause carries decision-relevant information.

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?

For a tool with no output schema and 0% parameter coverage, the description supplies both: it documents the full return shape (winning, yours, gaps, possibly_missing, fix_brief) and the error variant, and explains the fix_brief ordering. An agent has everything needed to call and interpret it.

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: it defines each of the 5 params with examples and defaults, and supplies the engine's value set ('chat_gpt', 'gemini', 'perplexity') plus country/language examples that the schema lacks entirely.

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+scope: comparing the user's own page structure against the AI-cited answer for a keyword and returning an actionable fix brief. It explicitly differentiates from the sibling analyze_citation_structure ('Use analyze_citation_structure instead if you just want the winning answer's shape'), so an agent can route without opening schemas.

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?

Gives explicit when-to-use framing ('what should I change on this page to get cited'), names two alternatives with their selecting conditions (analyze_citation_structure for the winner's shape; check_prompt_coverage first when several keywords and the missing ones are unknown). Nothing is left to inference.

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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