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Travel Airbnb

travel_airbnb
Read-only

Airbnb stays for a place and dates (first results page, usually 18): listing id, name, type, total price for the stay in the chosen currency (and original price when discounted), rating out of 5 with review count, beds/bathrooms, badges such as Guest favourite, free-cancellation note, coordinates and room URL. From Airbnb's public search page; availability and prices as Airbnb shows them at call time. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
adultsNoAdults, 1 to 16 (default 1)
checkinNoCheck-in date YYYY-MM-DD (optional; Airbnb picks flexible dates without it)
checkoutNoCheck-out date YYYY-MM-DD (needed with checkin)
currencyNoThree-letter currency code (default USD)
locationYesPlace, e.g. 'Paris, France' or 'Austin, TX'

Output Schema

NameRequiredDescriptionDefault
countNo
sourceNo
checkinNo
checkoutNo
currencyNo
listingsNo
locationNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses the results cap (~18, first page only), the data source (Airbnb's public search page), that prices/availability reflect call-time values, and a precise billing model ($0.002 USDC per successful call via x402, failures not charged). These are exactly the operational traits an agent cannot infer from annotations.

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?

Three sentences, front-loaded with what the tool returns, followed by source/freshness and then pricing. It is dense but every clause carries information; the field enumeration is long yet maps to real return values.

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 an output schema present and full parameter coverage, the description's gaps are minor. It covers data source, freshness, result-count limit, and payment model; the only missing piece is differentiation from sibling booking/review tools.

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 five parameters (adults, checkin, checkout, currency, location) are already documented in the schema. The description adds no syntax or format detail beyond that, 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?

The description clearly establishes the resource and the scope (Airbnb stays for a place and dates, first results page) and enumerates the returned fields, so an agent knows exactly what it gets. It stops short of explicitly distinguishing itself from travel_airbnb_reviews or the other booking-site siblings (booking_com, agoda, kayak).

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 statement of when to use this tool versus travel_airbnb_reviews or the competing hotel/booking siblings. The only usage-adjacent hint is “Airbnb's public search page” and “first results page,” which implies a browse-style search but doesn't route the agent between alternatives.

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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