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Google Search Remote MCP Server

by com.hasdata
OverviewDiscussionsAdmin

google_serp_ai_overview: GET /

hasdata_google_serp_ai_overview_getAiOverviewResponse
Read-only

Get AI Overview Results

Fetches the lazy-loaded Google AI Overview block via a pageToken returned by the Google SERP API (token valid for 1 minute). Returns the AI-generated answer text, referenced source URLs, and expanded subtopic sections. Use as a follow-up call to Google SERP for tracking AI citations in SEO, fact-checking answers against sources, and LLM retrieval pipelines grounded in live Google results.

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": {
      "pageToken": "<pageToken>"
    },
    "name": "hasdata_google_serp_ai_overview_getAiOverviewResponse"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageTokenYesToken from `aiOverview` block in Google SERP API. Valid for 1 minute.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / pageToken / description
      Previous value: -"Token from `aiOverview` block in Google SERP API. Valid for 4 minutes."New value: +"Token from `aiOverview` block in Google SERP API. Valid for 1 minute."
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, so safety is covered; the description adds the lazy-loaded nature, the 1-minute token window, and the shape of the payload (answer text, source URLs, expanded subtopics). It does not describe failure behavior when the token expires, which is the one notable gap.

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 a short title line followed by a dense but purposeful paragraph; every sentence carries either mechanism, timing, or use case. Slightly verbose in the final list of use cases but not wasteful.

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 correctly takes on the burden of describing the return payload, and it does so at a useful level of detail. A brief note on token-expiry failure handling would make it fully complete.

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?

Only one parameter and schema coverage is 100%, so the schema already documents pageToken fully. The description repeats the token's origin and 1-minute validity rather than adding format or edge-case detail beyond the 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?

States a specific verb (fetches) and resource (the lazy-loaded Google AI Overview block) and explains the mechanism (via a pageToken from Google SERP). An agent can distinguish this from hasdata_google_serp_serp_getSearchResults because the description frames it as a dependent follow-up rather than a primary search.

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?

Explicitly positions the tool as a follow-up call to Google SERP and names three concrete use cases (SEO AI-citation tracking, fact-checking, LLM grounding). No explicit 'do not use when' or named sibling alternative, but the context is unambiguous.

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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