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Start a collection

create_collection

Search a whole area, square by square, and collect up to maxPlaces of the places in it. Answers straight away with the collection, then works through the area in the background. Read the collection again to see how far it has got. Starting one costs nothing: each new place costs one credit as it arrives, and saved places cost nothing. Needs an API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoYesWhere to search. Give exactly one of: a Brazilian city as location, a lat/lng point with radiusM, a bbox, or a cityIbge with radiusKm.
langNoThe language to search in. New places come back in it. Two letters, such as pt or en.pt
enrichNoAdd ["emails"] to also look for email addresses. Costs one more credit for each place that has one, and needs a paid plan.
keywordsYesWhat to search for, such as ["bakery", "coffee shop"]. One search per term.
maxPlacesNoStop after this many places. Defaults to the most your plan collects at once.
minRatingNoKeep only places rated at least this, from 1 to 5. Null keeps every place.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=false, destructiveHint=false and openWorldHint=true; the description adds genuinely new behavior: asynchronous fire-and-return semantics, the credit cost model (free to start, one credit per arriving place, saved places free), and the API key requirement. This is exactly the extra context annotations cannot convey.

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?

Six short sentences, front-loaded with the purpose before the async and cost details. Nearly every sentence earns its place, though the cost sentence repeats 'costs nothing' twice and could be tightened.

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?

With no output schema, the description carries the return-value burden and does so ('answers straight away with the collection', re-read to see progress), and it covers auth and billing. It omits what happens on failure and never points at cancel_collection for stopping a run, which a long-running async job would benefit from.

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 adds economic semantics that the schema lacks: maxPlaces caps how many billable places arrive, and the enrich/credit relationship is hinted at ('each new place costs one credit'). It also frames the geo argument as 'a whole area', reinforcing the area-based search model.

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 and resource: search an area square by square and collect places into a collection, capped at maxPlaces. An agent can tell this is the asynchronous 'start a bulk collection' tool rather than a point lookup. It never names a sibling (search_places, quote_collection, get_collection) explicitly, so it falls short of full sibling differentiation.

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?

Gives clear operational context: the call returns immediately with the collection, then runs in the background, and the agent should re-read the collection to check progress. That tells an agent how to use the result. It stops short of naming alternatives (e.g. quote_collection to estimate cost before committing, or search_places for immediate one-off results).

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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