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pisanuw

Google Flights MCP

by pisanuw

search_multi_city

Search multi-city flight itineraries by providing ordered legs with departure, arrival, and date, and filter results by travel class, stops, and passengers.

Instructions

Search a multi-city Google Flights itinerary (2+ separate legs).

Args: legs: Ordered list of leg objects, each with "departure_id", "arrival_id", and "date" (YYYY-MM-DD). For example: [{"departure_id": "SEA", "arrival_id": "NRT", "date": "2026-10-03"}, {"departure_id": "NRT", "arrival_id": "ICN", "date": "2026-10-10"}, {"departure_id": "ICN", "arrival_id": "SEA", "date": "2026-10-17"}] travel_class, adults, children, infants_in_seat, infants_on_lap, stops, max_price, currency, max_results, deep_search: as in search_flights.

Each option's departure_token can be passed to get_return_flights to advance to the next leg's options.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
legsYes
stopsNoany
adultsNo
childrenNo
currencyNoUSD
max_priceNo
deep_searchNo
max_resultsNo
travel_classNoeconomy
infants_on_lapNo
infants_in_seatNo
Behavior3/5

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

With no annotations, the description carries the burden. It discloses the chaining behavior (departure_token to get_return_flights) and gives an example, but it omits return format, pagination, and read-only nature. This provides some transparency but not full coverage.

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 description is well-structured with a clear one-line purpose, a focused Args section, and a concrete example. The cross-reference keeps it concise while ensuring the key parameter is thoroughly explained.

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?

For a multi-leg search with chaining, it covers essential context: legs structure, shared parameters, and next-step token usage. It doesn't describe the output format, but given the tool's complexity and lack of output schema, it is reasonably complete.

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 0%, so the description compensates by giving a detailed, illustrated definition for the necessary 'legs' parameter. The reference to search_flights for the remaining ten shared parameters is a meaningful cross-reference, though not fully self-contained.

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 uses a specific verb 'Search' with a clear resource 'multi-city Google Flights itinerary (2+ separate legs)', which distinguishes it from single-flight search tools like search_flights. The explicit '2+ separate legs' scopes the tool precisely.

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 clearly indicates multi-leg itineraries are the target and provides a chaining hint to get_return_flights via departure_token. However, it doesn't explicitly state when to prefer this over search_flights or list exclusions.

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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