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Get AI citation sources

get_ai_visibility_citations
Read-only

Read which domains and pages AI answers cite, and the domains that never mention the brand.

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": {
      "projectId": "<projectId>",
      "siteId": "<siteId>"
    },
    "name": "get_ai_visibility_citations"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNo
fromNo
engineNo
siteIdYes
enginesNo
categoryNo
monitorIdNo
projectIdYes
categoriesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds that it returns both cited domains/pages and domains that never mention the brand, which is useful context, but it does not disclose permissions, rate limits, or output format details. With annotations covering the basics, a 3 is appropriate.

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 a single, front-loaded sentence that covers the core purpose without any wasted words.

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

Completeness2/5

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

For a tool with 9 parameters, no output schema, and no parameter descriptions, the one-sentence description is insufficient. It lacks crucial details about filtering options and return structure that an agent would need to call the tool effectively.

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

Parameters1/5

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

There are 9 parameters with 0% schema description coverage, and the description mentions none of them (date range, engine, category, monitorId, projectId, siteId). It provides no meaning beyond what the parameter names alone suggest, leaving a significant gap for an agent trying to invoke the tool correctly.

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?

The description states a specific verb ('Read') and resource ('which domains and pages AI answers cite, and the domains that never mention the brand'), making the tool's output clear. It doesn't explicitly name sibling tools like get_ai_visibility_domain_pages or get_ai_visibility_overview, but the scope is distinct enough for an agent to differentiate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus the many other AI visibility tools (e.g., get_ai_visibility_domain_pages, get_ai_visibility_overview). No prerequisites, exclusions, or alternative selection criteria are given.

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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