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pangolinfo

Amazon All-in-One Scrape MCP

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search_local_maps

Search local businesses on Google Maps by specifying a location and query. Returns detailed business data including ratings, reviews, and addresses.

Instructions

[Local Maps via Google Maps] Local-business search (data source: Google Maps; use must comply with Google Terms of Service). Search local businesses at a given lat/lng — returns name, address, rating, review count, etc. Use when: user says "Y businesses in city X" / "local retail research" / "offline channel distribution" / "coffee shops/supermarkets/wholesalers in area" / "physical-store coverage density"; offline competitor/channel research; gauging physical-supply density of a category in a region. Don't use: for e-commerce listings (Amazon series); for global trends (use keyword_trends); for Google search results (use ai_search). Returns: data.organicResults[{ place_id, name, about, rating, number_of_reviews, borough, street_addr, city, postal_code, ... }]. Pair with: ↑ query (business keyword) + latitude/longitude/zoom (zoom 1=world, 13=city, 21=single building); ↓ presentation-focused, downstream rarely consumes. Cost: ~1.5 points/call, ~5s. Tips: zoom 13 (city, default) gives you a whole neighborhood; zoom 17+ narrows to one street.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesLocal search query. Examples: 'coffee shop' / 'wholesale electronics' / '电子产品批发' / 'pet store'.
latitudeYesLatitude of search center. Examples: 37.7822 (San Francisco) / 40.7128 (New York) / 34.0522 (Los Angeles).
longitudeYesLongitude of search center. Examples: -122.4642 (San Francisco) / -74.0060 (New York) / -118.2437 (Los Angeles).
zoomNoMap zoom level, 1=world, 13=city, 21=building. Default 13.
languageNoBCP-47 language code, e.g. 'en', 'zh-CN'.en
limitNoMax results to return (1-100).
Behavior4/5

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

Discloses data source (Google Maps), cost (~1.5 points), latency (~5s), and zoom behavior tips. No annotations provided, so description carries burden; lacks details on authentication or rate limits.

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?

Well-structured with clear sections, front-loaded purpose. Slightly verbose but every sentence adds value; appropriate for tool complexity.

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?

Covers purpose, usage, return structure, cost, tips. No output schema, so return description is helpful but could elaborate on field semantics. Overall adequate for a search tool.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. Description adds value with zoom level usage examples ('13 gives neighborhood, 17+ narrows to street') and pairing hints. Slightly above baseline.

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?

Clearly states 'Local-business search' at a lat/lng, lists returned fields, and distinguishes from sibling tools like ai_search and keyword_trends with explicit 'Don't use' instructions.

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

Usage Guidelines5/5

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

Provides explicit 'Use when' and 'Don't use' sections with concrete examples and alternatives (e.g., 'use keyword_trends' for global trends), plus pairing advice.

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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