Scrapingdog MCP Server

Google AI Overview API

google_ai_overview

Fetch the Google AI Overview block for a search query using a temporary URL from a google_search response. Retrieve the AI-generated summary before the URL expires.

Instructions

Fetch the Google AI Overview block for a search. Pass the AI-overview URL returned in a google_search response (that URL expires ~2 minutes after it is issued).

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": {
      "url": "<url>"
    },
    "name": "google_ai_overview"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	AI Overview URL taken from a google_search response. Expires ~2 minutes after issuance.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 1, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It discloses the URL expiry (~2 minutes), which is critical context. However, it does not describe the response format, error behavior, or any rate limits, leaving gaps for a fetch tool.

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 two sentences, front-loaded with the main action, and contains no filler. It efficiently conveys the purpose and the key usage constraint.

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?

For a simple single-parameter tool, the description covers the what, how, and a critical temporal constraint. However, the absence of an output schema means the description could have mentioned the expected return format, but this is a minor gap given the tool's simplicity.

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?

The schema already provides a complete description of the 'url' parameter (source and expiry). The tool description essentially repeats this information without adding new semantics, so the baseline score of 3 applies.

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?

The description clearly states the tool's action ('Fetch the Google AI Overview block') and its specific resource ('for a search'). It distinguishes itself from siblings by referencing the AI-overview URL from google_search responses, which clarifies its role in the search workflow.

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?

The description gives clear context: use this after a google_search to fetch the AI Overview block using the returned URL. It does not explicitly exclude alternatives or mention when not to use, so it falls 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.