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vantagemcp

vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Compare your page with the cited answer

analyze_citation_gap
Read-onlyIdempotent

Compare your page against the AI-cited answer for a keyword, then get ordered rewrite steps to close citation gaps.

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'. The fix brief 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.

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

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

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, and the description's 'Read-only: no side effects, safe to retry' largely restates them. The genuinely additive information is the metering model (1 quota unit per call, 30 units/month shared across all metered tools) and the error return path, which are useful behavioral context the annotations cannot convey.

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 purpose and the differentiating use case before the long return-shape block, and the formatting/args sections are scannable. It is verbose in places ('not just a description of the winner', the parenthetical about page shape vs. citations) where a clause would do, but the length is largely justified by 0% schema coverage and no output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description supplies the full return contract (keyword, your_url, winning, yours, gaps, possibly_missing, fix_brief ordering, plus the error case) and covers all five parameters. Remaining gaps are minor: no enumeration of valid country values, and no statement about URL accessibility requirements or how keyword matching is performed.

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 description coverage is 0%, so the description carries the parameter burden and mostly does: it gives an example keyword and URL, explains country as the market the cited answer is read in, language as a code with default, and enumerates engine's values (chat_gpt default, gemini, perplexity) which the schema does not. It leaves country's accepted value space unenumerated, which is the main gap.

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 (compare your page against the AI-cited answer for a keyword) and adds a distinctive deliverable: an ordered 'fix brief' of rewrite instructions rather than a description of the winner. This clearly separates it from analyze_citation_structure, whose shape it reuses but does not duplicate.

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 explicit usage framing: use this to answer 'what should I change on this page to get cited' rather than 'what does a winning answer look like', which routes the agent away from the structure-only sibling. It also sets a boundary ('the fix brief never contains the cited answer's text'). It does not name the competing sibling tools outright as alternatives, so it stops short of a 5.

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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