Scrapingdog MCP Server

Google Shopping API

google_shopping

Scrape Google Shopping product listings and prices. Get parsed JSON or raw HTML for any product query, with geo-targeting and language filters.

Instructions

Scrape product listings and prices from Google Shopping.

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": {
      "query": "<query>"
    },
    "name": "google_shopping"
  }
}

Input Schema

Name	Required	Description
`tbs`	No	Advanced result filter.
`html`	No	Return raw HTML instead of parsed JSON. (API default: false)
`page`	No	Zero-based page number. (API default: 0)
`safe`	No	Adult-content filter. (API default: off)
`query`	Yes	Product search term.
`domain`	No	Country-specific Google domain (e.g. google.co.uk, google.co.in). (API default: google.com)
`country`	No	Two-letter ISO country code to geo-target results (e.g. us, gb, in, de). (API default: us)
`language`	No	Result language code (e.g. en, es, fr, de). (API default: en)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 1, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries full responsibility for disclosing behavior. It only says 'scrape' without explaining output format, pagination, rate limits, or other operational traits. This is a minimal disclosure that leaves significant behavioral aspects undisclosed.

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 sentence with no redundant words. It is front-loaded with the action and subject, making it highly concise and easy to parse. Every word contributes meaning.

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?

With 8 parameters, no annotations, and no output schema, the one-line description is insufficient. It does not explain return value structure, pagination behavior, or how parameters like domain, country, and language affect results, leaving significant gaps for an agent to use the tool correctly.

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 input schema has 100% parameter description coverage, so the baseline is 3. The tool description adds no additional parameter semantics beyond what the schema already provides, but it also does not need to, given the schema's completeness.

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 'Scrape product listings and prices from Google Shopping' uses a specific verb ('scrape') and resource ('product listings and prices from Google Shopping'), clearly distinguishing it from sibling tools like google_search or amazon_search. It is precise and unambiguous.

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?

No usage guidance is provided. The description does not indicate when to use this tool instead of alternatives, nor does it mention any exclusions or prerequisites. It simply states what it does, leaving the agent without contextual direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.