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google_maps_posts: GET /

hasdata_google_maps_posts_getMapPosts

Get Map Posts

Fetches the latest Google Maps Posts (timeline-style updates such as offers, events, announcements, and notices) for a place by dataId or placeId, with language targeting. Returns per-post title, description, image, posted_at, link, and source/business name. Use for small-business intelligence, local-marketing monitoring, competitor activity tracking, and surfacing current promotions and events from local merchants.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hlNoThe two-letter language code for the language you want to use for the search. Provide one exact documented value (159 allowed), e.g. `af`, `ak`.
dataIdNoGoogle Maps data ID.
placeIdNoUnique reference to a place on a Google Map. Either dataId or placeId should be set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / nextPageToken
      Removed value: -{
      -  "description": "Defines the next page token. It is used for retrieving the next page results.",
      -  "type": "string"
      -}
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It does disclose the return shape (title, description, image, posted_at, link, source/business name) and implies a safe read via 'Fetches', but says nothing about auth, rate limits, or pagination/result-count behavior.

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?

Front-loaded with the purpose, then the return fields, then the use cases – a sensible order. The trailing use-case list is slightly padded but each clause is relevant, so it is efficient without being maximally tight.

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?

There is no output schema, so describing the returned per-post fields is genuinely valuable and fills that gap. For a read tool with three fully documented params, the main missing piece is pagination/volume behavior, which keeps it from a 5.

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?

Schema coverage is 100% and the schema already documents hl, dataId, and placeId with their semantics. The description adds only a light 'either dataId or placeId' routing hint and 'language targeting', which is roughly the schema's own content, so the baseline 3 applies.

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?

States a specific verb+resource: 'Fetches the latest Google Maps Posts ... for a place by dataId or placeId,' and the parenthetical ('offers, events, announcements, notices') disambiguates what 'Posts' means versus reviews/photos/place details. It never explicitly names the sibling tools it differs from, so it stays at 4 rather than a full 5.

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

Usage Guidelines3/5

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

Provides use-case context ('small-business intelligence, local-marketing monitoring, competitor activity tracking'), which implies when the tool is relevant. It gives no when-not guidance and no explicit routing against the many Google Maps siblings (place, reviews, photos), so usage is only implied rather than prescribed.

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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