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Crawlora MCP

airbnb_search

Read-only

Airbnb listing search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoResult page, 1-based, default 1.
zoomNoMap zoom level used with the bounding box, default 11.
adultsNoNumber of adult guests; only applied when greater than 0.
ne_latNoNortheast corner latitude of the map bounding box; set all four ne/sw lat/lng for map-bounded search.
ne_lngNoNortheast corner longitude of the map bounding box; set all four ne/sw lat/lng for map-bounded search.
sw_latNoSouthwest corner latitude of the map bounding box; set all four ne/sw lat/lng for map-bounded search.
sw_lngNoSouthwest corner longitude of the map bounding box; set all four ne/sw lat/lng for map-bounded search.
check_inNoCheck-in date, YYYY-MM-DD; pair with check_out.
currencyNoISO-4217 currency code for prices, e.g. USD.
locationYesRequired search location, e.g. New York, NY.
check_outNoCheck-out date, YYYY-MM-DD; pair with check_in.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.4/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-data scope are covered. The description adds nothing beyond that - no mention of pagination behavior, result volume, rate limits, or how the map-bounding-box mode differs from a text location search.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a three-word sentence fragment. Brevity is not the problem - under-specification is: it front-loads nothing useful and conveys no information an agent could not get from the tool name alone.

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

Completeness2/5

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

This is a complex tool (11 parameters, open-world search) with an output schema, so return values need not be described, but the description still omits everything about when the tool applies, how location and bounding box interact, and how it differs from the many alternative lodging searches.

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 description coverage is 100%, so all 11 parameters are self-documented (dates pairing, bounding-box corners, page, zoom, adults, currency). The description contributes no additional parameter meaning, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a verb and resource ('listing search' on Airbnb), so the agent knows it returns Airbnb listings rather than hosts or rooms. However, it is nearly a restatement of the tool name and gives no differentiation from siblings like airbnb_host_listings, airbnb_room, or datasets_airbnb_search.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus the many sibling search tools (agoda_hotels_search, booking_search, vrbo_search, datasets_airbnb_search), nor any mention of prerequisites such as requiring a location. The agent must infer usage entirely.

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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