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Google Flights MCP Server

MCP Server

Connect AI agents to real-time flight data quickly

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Updated 12 days ago

About

A Model Context Protocol server that lets AI agents retrieve, filter, and compare flight options from Google Flights, including cheapest, best‑rated, and time‑filtered results.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Google Flights MCP Server is a lightweight bridge that exposes real‑time flight data from Google Flights to AI agents via the Model Context Protocol. By turning flight search into a set of deterministic, queryable functions, it removes the need for agents to parse web pages or scrape data themselves. This is especially valuable in scenarios where an assistant must deliver flight recommendations, price comparisons, or itinerary planning without exposing users to the complexity of airline APIs.

At its core, the server offers four focused tools:

  • returns up to forty detailed flight options for a requested route, including times, layovers, and carrier information.
  • sorts those options by price, giving agents a quick way to surface the most affordable tickets.
  • surfaces flights that Google Flights marks as “best” based on factors such as price, duration, and convenience.
  • lets agents narrow results to flights arriving or departing before/after a user‑specified time, enabling precise scheduling.

These functions are parameterised with the essential flight details—origin, destination, departure date—and enriched by optional settings for seat class, passenger counts, and trip type. Although the current implementation supports only one‑way trips (round‑trips are simulated as two separate searches), the design is modular enough for future expansion to multi‑city or round‑trip queries.

For developers, the server’s value lies in its seamless integration with existing MCP‑enabled workflows. An LLM can call the appropriate tool, receive structured JSON, and then compose a natural‑language response or build an itinerary. The server’s strict input schema ensures that agents receive consistent, error‑free data, while the clear separation of concerns (search vs. filtering) keeps reasoning pipelines clean.

Real‑world use cases include:

  • Travel agencies automating flight suggestions for clients.
  • Productivity assistants scheduling business trips on the fly.
  • Chatbot integrations that answer “What are my cheapest flights from LAX to Tokyo on 2025‑06‑15?” in seconds.
  • Travel research tools that compare multiple routes and seat classes for cost optimisation.

Because the server taps directly into Google Flights’ live data, users benefit from up‑to‑date pricing and availability without having to manage API keys or third‑party rate limits. Its straightforward MCP interface makes it an attractive component for any AI stack that requires dynamic travel information, offering a blend of speed, reliability, and developer‑friendly design.