Google Flights Protobuf MCP

Reverse engineered Google Flights and coded a lil smth to help plan my flights across Europe!

A standalone MCP server for this deliberately bounded pipeline:

protobuf tfs query
  -> browser-impersonating HTTP discovery
  -> outbound/return pairing
  -> deterministic ranking
  -> top 1-3 exact /booking?tfs= links
  -> Playwright price + itinerary verification

How the protobuf reverse-engineering works

Google Flights does not expose a supported public shopping API. Its web UI stores the search state in the tfs query parameter used by URLs such as:

https://www.google.com/travel/flights/search?tfs=<URL_SAFE_BASE64>&hl=en&gl=PT&curr=EUR

The tfs value is a serialized Protocol Buffers message encoded with URL-safe Base64 and stripped of trailing = padding. The schema in flights.proto is inferred from the web application; it is not published or guaranteed by Google.

The encoder follows this path:

SearchRequest
  -> Info protobuf
      -> FlightData for each direction
      -> airports, dates, stops, airlines and time filters
      -> passengers, cabin, baggage, trip type and maximum price
  -> SerializeToString()
  -> URL-safe Base64 without padding
  -> /travel/flights/search?tfs=...

Important inferred fields include:

The schema was reconstructed by changing one Google Flights control at a time, decoding the resulting Base64 tokens, comparing protobuf wire tags, and then validating the inferred type and field number by generating a new URL. Unknown booking-only fields retain neutral names such as marker_one; the project does not claim semantics that have not been demonstrated.

Why complete itinerary pairing takes two searches

A return fare cannot safely be produced by adding the cheapest outbound and cheapest inbound. Google reprices the trip after the outbound is selected. This project therefore:

1. searches and parses the available outbound directions;

2. embeds one selected outbound in field 4 of the outbound FlightData;

3. requests the repriced inbound choices for that selection;

4. pairs each inbound with that outbound and keeps Google's combined total;

5. embeds every physical leg from both directions in a booking tfs token.

This creates a deep link for one complete itinerary instead of a generic route/date search. Search-page prices are still discovery quotes until the Playwright verifier confirms the rendered total and provider handoff.

HTTP discovery is not an API

The fast discovery layer requests the normal Google Flights HTML using a browser-compatible TLS fingerprint. It extracts the embedded ds:1 data from AF_initDataCallback, parses both the top and other-flight groups, and rejects consent pages, CAPTCHA responses, malformed payloads, and airport substitutions. There is no stable JSON endpoint involved.

Google can change the protobuf schema, the embedded array layout, consent handling, or anti-automation policy at any time. The parsers are defensive, but this integration requires monitoring and should not be treated as a contracted production API. Use it responsibly and comply with Google's terms and applicable law.

The original public demonstration of this general tfs protobuf technique is the AWeirdDev/flights project. This repository reimplements the schema and adds complete itinerary pairing, ranking, explicit verification states, MCP tools, the semester scanner, and the Railway dashboard.

Related MCP server: google-flights-mcp

Install and run

cd google-flights-proto-mcp
uv sync --all-extras
uv run google-flights-proto-mcp

For streamable HTTP MCP:

uv run google-flights-proto-mcp-http

The default endpoint is http://127.0.0.1:8010/mcp/. HTTP clients must send:

Accept: application/json, text/event-stream

Set HOST and PORT to change the bind address. Browser discovery prefers an installed Chrome/Chromium automatically. Override it with:

export GOOGLE_FLIGHTS_MCP_BROWSER_EXECUTABLE=/path/to/chrome

If Google rotates its EU consent cookie, set GOOGLE_FLIGHTS_MCP_SOCS_COOKIE. The default is a consent-choice cookie, not an account/session credential.

MCP tools

• build_protobuf_search_url: builds a search URL without network access.

• discover_and_rank_complete: fast HTTP discovery, full round-trip pairing, ranking, and top 1-3 exact booking links. Its prices are explicitly marked as discovery prices.

• search_and_verify_top: the full pipeline. A price is verified only at shortlist[].verification.verified_price when verified is true.

The discovered_price is Google Flights' HTTP shopping price for a fully paired itinerary. It must never be relabelled as browser-verified. Exact booking URLs pin dates, airports, passengers, cabin, airlines, and flight numbers in protobuf; they do not freeze inventory or price.

Ranking

Ranking operates only on completed itinerary pairs:

• 50% total price

• 25% useful time at the destination

• 15% total flight time

• 10% stops

The initial outbound list is trimmed by price/stops/duration only to bound HTTP fan-out. That preliminary trim is not presented as the final ranking.

Verification contract

Playwright opens the exact /travel/flights/booking?tfs=... page and requires:

• the rendered Lowest total price amount;

• the encoded passenger count and cabin;

• all encoded flight legs and dates;

• Google's required-taxes-and-fees notice;

• a same-priced booking option and a successful provider handoff that repeats the same total.

On any mismatch or anti-automation challenge, verified_price remains null. Even a provider-confirmed price can change before purchase, and optional baggage or payment charges may still apply.

Fast weekend price scanner (no MCP, no Playwright)

For broad destination discovery, use the search-page scanner directly:

uv run python scripts/search_weekend_prices.py --top 5 --workers 4

The scanner defaults to one adult. Override it explicitly with --adults N when a different passenger count is needed.

It reads config/semester_2026.json, generates one /travel/flights/search?tfs=<protobuf> URL per airport/weekend, fetches the embedded Google search results, rejects alternate-airport substitutions, and writes ranked JSON and CSV files under outputs/.

Useful overrides:

uv run python scripts/search_weekend_prices.py \
  --weekend '25–28 Sep' \
  --destinations BCN,FNC,NCE,MAD \
  --max-stops 1 \
  --max-price 500 \
  --airlines U2,VY,FR

These are live Google search-page quotes, not checkout-verified prices. The scanner records anti-automation failures separately and never converts a blocked query into a false “no flights” result.

Travel windows can include an availability_note plus earliest outbound and return hours. Exam-day windows use a realistic airport buffer: an assessment ending at 19:30 does not permit a 21:00 departure. When Friday has no exam, the corresponding search window starts at 23:00 on Thursday so a useful extra evening flight is eligible without assuming the traveller is free earlier that day.

Bucket-list deal ranking

After scanning the bucket-list airport universe, compare every destination with its own median quote across the semester windows and build the coverage-first plan:

uv run python scripts/rank_bucket_deals.py

The output calls this baseline semester_window_median. It is an auditable comparison within this scan, not Google's historical “typical price” signal.

Hourly Google Sheet refresh on macOS

scripts/refresh_google_sheet.py runs the bucket-airport scan for one adult, retries transient failures, recalculates route medians, ranks every eligible option, publishes the top three per weekend to the Sheet, and overwrites only the values in 3 per Weekend!A2 and 3 per Weekend!A5:N43. Existing formatting and conditional-format rules are preserved. The last good Sheet remains untouched if the scan is incomplete. The default retry policy uses two workers and paced backoff because a complete 104-destination scan across 13 windows makes 1,352 Google searches and can encounter HTTP 429 responses.

The job uses the official Google Sheets API for workbook writes. Create a Google Cloud service account, enable the Google Sheets API, download its JSON key outside this repository, and share the workbook with the service account's client_email as an editor. Then test without changing the Sheet:

GOOGLE_APPLICATION_CREDENTIALS=/absolute/path/to/service-account.json \
  uv run python scripts/refresh_google_sheet.py --dry-run

Run one real refresh:

GOOGLE_APPLICATION_CREDENTIALS=/absolute/path/to/service-account.json \
  uv run python scripts/refresh_google_sheet.py

For an hourly macOS job, copy com.kasperhong.fli-sheet-refresh.plist.example to /Users/kasperhong/Library/LaunchAgents/com.kasperhong.fli-sheet-refresh.plist, change the credentials path if needed, and load it:

launchctl bootstrap gui/$(id -u) \
  /Users/kasperhong/Library/LaunchAgents/com.kasperhong.fli-sheet-refresh.plist

Inspect the log at outputs/hourly-refresh.log. To reload after editing the plist, boot it out first and then bootstrap it again:

launchctl bootout gui/$(id -u) \
  /Users/kasperhong/Library/LaunchAgents/com.kasperhong.fli-sheet-refresh.plist

The hourly rows remain Google search-page quotes. Provider-checkout Playwright verification is intentionally not run across the full route universe each hour; that should be limited to the current top one to three candidates.

Railway website

The Railway-ready FastAPI dashboard serves the last successful snapshot immediately and refreshes prices in the background. It includes:

• every realistic option found under the hard €250 return ceiling, with the top three shown by default, a global Top 3 / All options switch, and per-weekend expansion;

• exact one-adult protobuf Google Flights links;

• hourly scanning, median recalculation, and reranking;

• atomic snapshot publishing so blocked scans never replace good data;

• /healthz, /api/status, and /api/deals endpoints;

• an optional token-protected POST /api/refresh endpoint.

Run it locally without starting background Google searches:

FLI_REFRESH_ENABLED=false uv run google-flights-proto-web

Then open http://127.0.0.1:8000.

For Railway, deploy this directory as the service root. Railway detects the included Dockerfile, starts the server on its injected PORT, and checks /healthz. Add a persistent volume mounted at /data so successful snapshots survive deployments. Use one replica; multiple replicas would each run their own scanner.

Optional Railway variables:

Manual refresh, when FLI_ADMIN_TOKEN is configured:

curl -X POST -H "X-Refresh-Token: YOUR_TOKEN" \
  https://YOUR-DOMAIN/api/refresh

The website intentionally labels prices as search-page quotes. Hosting does not turn them into checkout-verified fares, and Railway datacenter IPs may be rate-limited more often than a residential connection.