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Darshan972

Scrapingdog MCP Server

by Darshan972

Google Maps API

google_maps

Retrieve local business listings and place details from Google Maps using search queries, location coordinates, and filters. Get structured data on names, addresses, ratings, and more.

Instructions

Scrape local business listings and place details from Google Maps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
llNoGPS origin as @latitude,longitude,zoom (e.g. @40.7,-74.0,14z). Required for pagination.
dataNoGoogle Maps 'data' filter string copied from a Maps URL.
pageNoPagination offset; increment by 20. Requires ll. (API default: 0)
typeNoResult type.
queryYesGoogle Maps search query, e.g. 'pizza'.
domainNoCountry-specific Google domain (e.g. google.co.uk, google.co.in). (API default: google.com)
countryNoTwo-letter ISO country code to geo-target results (e.g. us, gb, in, de). (API default: us)
languageNoResult language code (e.g. en, es, fr, de). (API default: en)
place_idNoUnique Google Maps place identifier (for place lookups).
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'scrape' and gives no information about rate limits, pagination behavior, authentication requirements, or data output format, which is a significant gap for an agent.

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, clear sentence that immediately conveys the tool's purpose. No filler or unnecessary repetition exists, making it appropriately concise and front-loaded.

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?

Despite full schema coverage, the tool has 9 parameters and no annotations or output schema. The description lacks context about how scraping works, typical usage patterns, pagination, or what the results look like, making it incomplete for an agent to safely and effectively invoke.

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 provides descriptions for all 9 parameters with 100% coverage, so the baseline is 3. The description adds no extra parameter semantics beyond what the schema already documents, such as the meaning of 'll' or 'data'.

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 clearly identifies the action ('scrape') and resource ('local business listings and place details from Google Maps'). It specifies the domain, but does not explicitly contrast with sibling tools like google_search or web_scrape, so it lacks strong differentiation.

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 guidance is provided on when to use this tool versus alternatives. The description does not mention use cases, prerequisites, or exclusions, leaving the agent to infer suitability from the name alone.

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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