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Argosor — Unified SEO, SERP, Clean Markdown & GEO (AI Citation Visibility) MCP Server

by com.argosor
OverviewDiscussionsAdmin

Backlink Authority & LLM Citation Graph

backlink_authority_graph
Read-onlyIdempotent

Inspect a domain backlink authority profile and generative AI citation graph across referring domains and authoritative web sources. Use this tool to evaluate Domain Rating, link velocity, anchor text diversity, and which URLs on a domain are most frequently cited by LLMs. Returns Domain Rating (0-100), referring domain counts, dofollow/nofollow ratios, spam risk score, anchor text distribution, and top AI-cited pages.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "backlink_authority_graph"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesTarget root domain or hostname to analyze (e.g., "argosor.com").
include_llm_cited_pagesNoWhen true, includes the top URLs on the domain most frequently cited by Perplexity, ChatGPT Search, and Claude (default: true).
include_anchor_distributionNoWhen true, includes the categorized anchor text percentage breakdown (default: true).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / properties / domain / maxLength
      Added value: +253
    • addedInput schema / properties / domain / minLength
      Added value: +3
    • removedInput schema / properties / includeAnchorDistribution
      Removed value: -{
-  "description": "When true, includes categorized anchor text percentage breakdown. Defaults to true.",
-  "type": "boolean"
-}
    • removedInput schema / properties / includeLlmCitedPages
      Removed value: -{
-  "description": "When true, includes the top URLs on the domain most frequently cited by Perplexity, ChatGPT Search, and Claude. Defaults to true.",
-  "type": "boolean"
-}
    • addedInput schema / properties / include_anchor_distribution
      Added value: +{
+  "default": true,
+  "description": "When true, includes the categorized anchor text percentage breakdown (default: true).",
+  "type": "boolean"
+}
    • addedInput schema / properties / include_llm_cited_pages
      Added value: +{
+  "default": true,
+  "description": "When true, includes the top URLs on the domain most frequently cited by Perplexity, ChatGPT Search, and Claude (default: true).",
+  "type": "boolean"
+}
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. Because no output schema exists, the description adds real value by disclosing the exact shape of the result (DR 0-100, dofollow/nofollow ratios, spam risk score, anchor distribution, top AI-cited pages). It omits cost, rate limits, and freshness/caching behavior, which keeps it below 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 front-loaded sentences with no filler: capability, usage, and output shape in that order. The usage sentence and the returns sentence overlap slightly on anchor text and AI-cited pages, which is the only redundancy.

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 explicit return-value enumeration is what makes this callable with confidence, and it is present. Minor gaps remain around how "domain" is normalized and whether results are cached or point-in-time, but nothing essential for correct invocation is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so all three parameters are already documented, including the two booleans and their defaults. The description alludes to what those toggles unlock (anchor text diversity, AI-cited pages) but adds no syntax, cost, or trade-off detail beyond the schema; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource: inspecting a domain's backlink authority profile plus an LLM citation graph, and enumerates the specific metrics produced (Domain Rating, referring domains, spam risk). It is unambiguous about what the tool does, but it never names a sibling such as geo_llm_visibility_audit or competitor_gap_matrix to delineate the boundary between backlink authority and general GEO/competitor analysis.

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?

"Use this tool to evaluate Domain Rating, link velocity, anchor text diversity, and which URLs on a domain are most frequently cited by LLMs" gives a clear selection context. There are no exclusions or named alternatives, so an agent must infer the boundary with siblings on its own.

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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