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google-flights-mcp

google-flights-mcp

by ThiagoJacobLannes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

search_flights

Find and compare flight prices and options on Google Flights for one-way or round-trip travel, with filters for stops, cabin class, passengers, and sorting by price or duration.

Instructions

Search flight prices and options on Google Flights.

Args: destination: Destination airport IATA code (e.g. "GRU"). If you only have a city name, call airport_search first. departure_date: Outbound date, YYYY-MM-DD. origin: Origin airport IATA code. Defaults to Lisbon (LIS) if omitted. return_date: Return date YYYY-MM-DD to search a round trip; omit for one-way. For round trips, each result's price is Google's estimated round-trip total for that outbound flight paired with its cheapest matching return — stops/duration/legs describe the outbound only. Open booking_link to pick the exact return flight. adults: Number of adult passengers (default 1). children: Number of child passengers (default 0). infants: Number of lap infants, under 2 with no own seat (default 0). cabin_class: "economy" | "premium" | "business" | "first". currency: ISO currency code. Defaults to EUR. max_stops: Maximum stops to allow (0 = nonstop only, 1 = up to one stop, etc.). Omit to allow any number of stops. sort_by: "price" (default, ascending) or "duration" (ascending).

Input Schema

NameRequiredDescriptionDefault
adultsNo
originNoLIS
infantsNo
sort_byNoprice
childrenNo
currencyNoEUR
max_stopsNo
cabin_classNoeconomy
destinationYes
return_dateNo
departure_dateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it explains the non-obvious round-trip pricing semantics, that stops/duration/legs describe only the outbound flight, and that booking_link is needed to choose the exact return. It still lacks details on errors, rate limits, or whether results are live/cached, but it is unusually transparent for a search tool.

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

Conciseness5/5

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

The purpose is front-loaded, and the remaining text is a compact parameter reference with no filler. Given 11 parameters and a nuanced round-trip pricing caveat, the length is justified.

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?

No output schema or annotations exist, so the description must explain both input and output expectations. It does well on inputs and hints at result fields (price, stops, duration, legs, booking_link), but it could more fully describe the return shape and any search limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: every one of the 11 parameters is documented with meaning, defaults, and examples, including IATA code examples, date format, passenger types, enum values, and max_stops semantics.

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?

The description opens with a specific verb and resource: 'Search flight prices and options on Google Flights.' It also distinguishes one sibling by directing city-only callers to airport_search, so an agent can identify the tool's scope immediately.

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?

It gives a clear usage rule: if you only have a city name, call airport_search first. However, it does not explain when to use this tool versus cheapest_dates, which is likely the relevant alternative for flexible-date searches.

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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