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Have the server fetch the reviews (spends a monthly server fetch)

fetch_place_reviews

Idempotent

Fallback for when you cannot reach a browser tab signed in to Google. Queues a server-side pull of the listing's newest reviews (the same worker as the site's form) and scores it. Ask the user first: it spends one of their server-side fetches for the month (check_place's serverFetch block says how many are left). Returns the job's progress; call again with job_id every 10-15 seconds until status is done (the result is then in the response) or failed (nothing is spent). Takes a Maps link, including share short-links, or a place_id. A place that is already scored returns its result without a fetch.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "fetch_place_reviews"
  }
}

Input Schema

Name	Required	Description
`url`	No	Alternative to place_id: any Google Maps place link, share short-links included (the server's browser expands them).
`job_id`	No	A job from an earlier call: returns its progress, or the result once done.
`place_id`	No	Google's feature id for the place (0x…:0x…, the '!1s' segment of a /maps/place URL).

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only declare the generic profile (readOnlyHint=false, idempotentHint=true, openWorldHint=true); the description adds the costly parts an agent cannot guess — it consumes one of the user's monthly server fetches, failures spend nothing, a cached score short-circuits the fetch, and the call is asynchronous via job_id. It also warns the agent to confirm with the user before spending quota.

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 fallback role, then cost warning, then polling loop, then accepted input forms — a sensible priority order. The single paragraph is dense and the polling instruction and cost warning sit mid-sentence, so a light restructure would help, but no sentence is filler.

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?

There is no output schema, and the description fills that gap by explaining the return value (job progress, then the result once status is done) and the failure case. Combined with the quota and idempotent-cache behavior, an agent has everything needed to invoke and re-invoke this tool correctly.

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%, so the baseline is 3, but the description contributes behavior the schema does not: job_id is not a one-shot input but a polling handle to re-call every 10-15 seconds until status is done or failed, and the three inputs are alternatives rather than cumulative. That polling contract is the main thing the schema alone would not convey.

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?

States a specific verb and resource — 'queues a server-side pull of the listing's newest reviews ... and scores it' — and frames it as a fallback rather than the primary path, which separates it from the browser-tab workflow and from siblings like check_place and list_scored_places.

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?

Gives an explicit when-to-use condition ('when you cannot reach a browser tab signed in to Google'), a prerequisite action ('Ask the user first'), a quota check pointer (check_place's serverFetch block), and the delivery path for already-scored places. No inference is left to the agent.

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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