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HasData

hasdata-mcp

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google_maps_photos: GET /

hasdata_google_maps_photos_getMapPhotos

Fetch Google Maps place photos using dataId or placeId, filterable by category and paginated. Get image URLs, thumbnails, and upload details for menu extraction or venue audits.

Instructions

Get Place Photos

Fetches the photo gallery of a Google Maps place by dataId or placeId, paginated with nextPageToken and filterable by categoryId (all, latest, menu, by owner, videos, street view). Returns each photo with image URL, thumbnail, upload date, uploader, and photoId. Use for restaurant-menu extraction, venue/ambience visual audits, building rich place detail pages, and sourcing up-to-date imagery for POI listings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataIdNoGoogle Maps data ID. Either dataId or placeId should be set.
placeIdNoUnique reference to a place on Google Maps. Either dataId or placeId should be set.
hlNoThe two-letter language code for the language you want to use for the search.
categoryIdNoFilters photos by category.
nextPageTokenNoToken for fetching the next page of photos.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses pagination (nextPageToken), filtering by categoryId, and return fields (image URL, thumbnail, etc.). It does not mention rate limits or exact page size, but covers core behavior well.

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, dense paragraph that front-loads the purpose, then details parameters and use cases. Every sentence adds useful information with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (pagination, filtering), the description covers inputs, outputs, and use cases thoroughly. No output schema exists, but the description lists return fields, making it complete.

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. The description adds value by explaining that dataId and placeId are alternatives, listing categoryId filter values (all, latest, menu, etc.), and specifying returned fields 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?

The description clearly states the tool fetches the photo gallery of a Google Maps place using dataId or placeId, and distinguishes from sibling tools like getPlaceDetails or reviews by focusing specifically on photos.

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 provides explicit use cases such as restaurant-menu extraction and venue visual audits, implicitly guiding when to use this tool over siblings. However, it lacks explicit 'when not to use' statements.

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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