ai.gondola/gondola

Tools

• compare_rates

  Compare cash vs points rates across multiple hotels side-by-side. Use this after search_hotels to help a user decide between their top hotel picks. Returns a comparison table with cash rate, points rate, CPP valuation, and value signals for each hotel, highlighting the best cash value and best points value. Args: hotel_ids: List of hotel IDs to compare (max 5). Get these from search_hotels results. checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. num_adults: Number of adult guests. Defaults to 2. Returns: Side-by-side comparison of cash vs points rates with recommendations.

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• credit_card_coverage

  Look up rental car CDW/LDW coverage provided by a credit card. Provide EITHER credit_card_product_name OR card_number_bin + card_provider. Args: credit_card_product_name: Exact card product name (preferred when known). card_number_bin: First 6-8 digits of the card number (BIN). card_provider: Card network ("visa", "mastercard", "amex", or "discover"). Required with card_number_bin. Returns: Coverage type, max days, and a human-readable summary.

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• diagnose_rates

  Diagnose rate availability and source statuses for a specific hotel. Use this to investigate why certain rates (e.g. AAA, member, points) are or aren't showing for a property. Shows per-supplier status and a full breakdown of every rate by type. Args: hotel_id: The hotel's Vervotech property ID. checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. num_adults: Number of adult guests. Defaults to 2. rate_sources: Optional comma-separated rate sources to check (e.g. "travelport", "direct,travelport"). If omitted, all sources are checked.

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• get_booking

  Get details for a specific hotel booking. Args: booking_id: The booking ID or confirmation number. Returns: Booking details including hotel, dates, room, rate, and status.

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• get_booking_link

  Get booking options for a hotel. Returns a link to Gondola's checkout for this hotel, where the traveler reviews the room and completes payment on the web. This is the booking path for this connection. (Connections belonging to an approved booking partner — which requires the mcp:book OAuth scope — additionally get an in-conversation option here. If you don't see booking tools in your tool list, this connection isn't one of those, and the link is the way to book.) Use this after search_hotels or get_hotel_details when a user wants to book. Pass ``gondola_rate_id`` whenever a specific rate has been surfaced (from get_hotel_details or compare_rates) so the link lands on that rate's checkout page instead of the generic hotel page. Args: hotel_id: The hotel's Vervotech property ID (from search_hotels results). checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. num_adults: Number of adult guests. Defaults to 2. children_ages: Comma-separated ages of children (e.g. "5,8"). Empty string if no children. gondola_rate_id: Optional rate ID from get_hotel_details/compare_rates. When provided, the link deep-links straight to that rate's checkout page. Returns: Booking instructions tailored to the user's auth status.

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• get_free_night_credits

  Get the user's free night certificates (award nights) across loyalty programs. Returns each certificate's program, how many remain, what it covers, when it expires, and whether a points top-up is allowed. Requires a Gondola account (API key). Returns: Formatted list of free night certificates, or instructions to connect.

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• get_hotel_details

  Get detailed information, room types, and rates for a specific hotel. Use this after search_hotels to get full details for a hotel the user is interested in. Returns room options with pricing, cancellation policies, and amenities. Args: hotel_id: The hotel's Vervotech property ID (returned by search_hotels). checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. num_adults: Number of adult guests. Defaults to 2. Returns: Detailed hotel information including rooms, rates, policies, and amenities.

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• get_hotel_reviews

  Get guest reviews for a specific hotel. Use this to help users understand what other guests thought about a hotel. Returns up to 10 recent reviews with ratings and comments. Args: hotel_id: The hotel's Vervotech property ID (from search results). Returns: Formatted list of guest reviews with author names, ratings, and review text.

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• get_hotel_stats

  Get pricing analytics and percentile data for a hotel rate. Use this to help users understand if a rate is a good deal. Shows how the cash rate and points redemption value compare historically across the chain. Args: hotel_id: The hotel's Vervotech property ID (from search results). nightly_cash_cost: The current nightly cash rate. nightly_cash_cost_currency: Currency of the cash rate (e.g. "USD", "EUR"). nightly_points_cost: Optional current nightly points cost. Returns: Pricing stats with percentile rankings and value assessment.

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• get_loyalty_accounts

  Get the user's hotel and airline loyalty accounts with points balances and values. Returns all linked loyalty accounts including current points balance, tier status, estimated cash value, recent points changes, and expiration dates. Requires a Gondola account (API key). Returns: Formatted list of loyalty accounts with balances and values, or instructions to connect.

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• get_multi_night_rates

  Get a rate calendar showing prices across a date range for a hotel. Use this when a user has flexible dates and wants to find the cheapest time to stay. Shows cash rates, points rates, and value percentiles for each available check-in date. Args: hotel_id: The hotel's Vervotech property ID (from search results). start_date: Start of date range in YYYY-MM-DD format. end_date: End of date range in YYYY-MM-DD format. nights: Number of nights per stay (default: 1). Returns: Rate calendar with pricing for each available date.

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• get_past_trips

  Get the user's past trips including hotel stays and flights. Returns a summary of past travel reservations with dates, confirmation numbers, status, costs, loyalty programs, routes, airlines, ticket class, miles redeemed, and historical flight seat assignments when Gondola parsed real row+letter seats from airline emails. Use this for trip-history questions, including favorite hotels, frequent routes, past airlines, raw seat-assignment evidence, and favorite-seat or aisle/window/side/row preference questions. Requires a Gondola account (API key). Args: limit: Max number of past trips to return, most recent first (default 20). The response notes how many more exist; raise this only when the user wants their full history. Returns: Formatted list of past trips, or instructions to connect an account.

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• get_rate_alerts

  Get all active rate alerts for the current user. Returns the user's rate alerts showing which hotels they're monitoring for price drops. Requires a Gondola account with an API key. Returns: List of active rate alerts with hotel names, dates, and current rates.

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• get_similar_hotels

  Find hotels similar to one the user is looking at. Use this when a user wants alternatives, comparisons, or asks "show me hotels like this one." Args: hotel_id: The hotel's Vervotech property ID (from search results). checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. num_adults: Number of adult guests (default: 2). Returns: List of similar hotels with rates and ratings.

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• get_suggested_searches

  Get personalized travel suggestions and trip inspiration. Returns curated hotel recommendations based on the user's preferences, recent searches, popular destinations, and upcoming holidays. Great for when the user doesn't know where to go. Returns: Travel suggestions with preview hotel results.

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• get_travel_profiles

  Get the user's saved travel profiles (guest name, email, and phone presets). Each profile has a selectable Profile ID, which prefills the guest name, email, and phone at checkout so the traveler doesn't re-enter them to prefill the guest details — the same "book as <traveler>" selection the website checkout offers — instead of collecting name, email, and phone field by field. Requires a Gondola account (API key). Returns: Formatted list of travel profiles with IDs, or instructions to add one.

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• get_traveler_context

  Get the user's saved travel context to personalize recommendations. Returns the user's loyalty programs and elite tiers, home airport, preferred airlines and cabin, preferred hotel chains, typical trip patterns (business vs leisure, budgets, frequent destinations), and any preferences they've stated or that have been learned from past conversations. Call this once at the start of a travel or planning session and weigh it across hotel, flight, and car recommendations — it is the single best source of who this traveler is. For raw evidence from actual past reservations, routes, hotels, airlines, or flight seats, use get_past_trips. Requires a Gondola account (API key). Returns: Formatted travel context, or instructions to build one.

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• get_upcoming_trips

  Get the user's upcoming trips including hotel stays, flights, and car rentals. Returns a summary of all upcoming travel reservations with dates, confirmation numbers, status, costs/rates, loyalty earnings, savings opportunities, AutoSave signals, flight segment details, miles redeemed, refundability/cancellation timing, and flight seat assignments when Gondola parsed real row+letter seats from airline emails. Requires a Gondola account (API key). Returns: Formatted list of upcoming trips, or instructions to connect an account.

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• get_vehicle_booking

  Get details for a specific vehicle booking. Args: booking_id: The Gondola booking ID (confirmation number). Returns: Vehicle booking details including vendor, pickup/dropoff, vehicle, rate, and status.

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• get_vehicle_booking_coverage

  Get the rental car CDW/LDW coverage stored at booking time for a vehicle booking. Args: booking_id: The Gondola booking ID of the vehicle booking. Returns: Coverage details stored on the booking, or an error message.

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• get_vehicle_booking_link

  Get a Gondola.ai deep link for a specific vehicle from search results. Returns a link to Gondola's checkout for this vehicle, where the traveler reviews the rate and completes the reservation on the web. This is the booking path for this connection. (Connections belonging to an approved booking partner — which requires the mcp:book OAuth scope — additionally get an in-conversation option here.) Args: search_id: Search ID from search_vehicles. vendor_code: Vendor code from search results. rate_code: Rate code of the selected vehicle. pickup_datetime: Pickup date and time in ISO format. dropoff_datetime: Drop-off date and time in ISO format. Returns: Booking instructions tailored to the user's auth status.

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• get_vehicle_details

  Get detailed information about a specific rental vehicle option. Use this after search_vehicles to get extras, insurance options, charges, and cancellation policy. Args: vendor_code: Vendor code from search results (e.g. "ZE" for Hertz, "AL" for Alamo). rate_code: Rate code from search results. search_id: Search ID from the vehicle search results. acriss_code: ACRISS code from the selected vehicle result. pickup_location: Pickup location from the selected vehicle result. vendor_location_id: Vendor desk identifier from the selected vehicle result. desk_kind: Desk classification from the selected vehicle result. Returns: Vehicle details including extras, charges, and policies.

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• optimize_loyalty_portfolio

  Analyze the user's whole loyalty portfolio and surface the highest-value actions. Trip-independent. Looks across every loyalty program the user holds — plus the transferable card currencies (Amex, Chase, Bilt, etc.) that can feed hotel programs — and reports points expiring soon (ranked by value at risk), the best transfer opportunities, and the largest balances. When the user's travel profile is available, it also tailors the view to their home airport, the airlines they fly, their frequent destinations, and when they travel (e.g. flagging points that expire before their usual travel months). Takes no arguments. Use this when the user asks how to make the most of their points, what's expiring, or where they can transfer. For deciding where to book a specific trip, use search_hotels / compare_rates instead. Returns: A Markdown portfolio summary, or instructions to connect accounts when none are linked.

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• predict_price

  Predict whether now is a good time to book a hotel, or if the user should wait for a better price. Uses historical price data and trends to assess whether the current price is a good deal. Call this when a user asks "Should I book now or wait?" or wants to know if a price is good. Args: hotel_id: The hotel's Vervotech property ID (from search results). checkin: Check-in date in YYYY-MM-DD format. checkout: Check-out date in YYYY-MM-DD format. nightly_cash_cost: The current nightly cash rate for the hotel. nightly_cash_cost_currency: Currency of the cash rate (e.g. "USD", "EUR"). nightly_points_cost: Optional current nightly points cost for the hotel. Returns: Price prediction with recommendation (book now vs wait), confidence level, and key signals.

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• search_events

  Search live events and return factual event, venue, date, and listed-price metadata.

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• search_flights

  Search for flights by route and date and return cash-priced options. Results are ranked for the traveler by the search backend — weighing their airline loyalty/status and travel history alongside flight quality — and returned 10 per page. To see more options, call again with ``page=2``, ``page=3``, and so on. Args: origin: Origin airport code or city (e.g. "LAX", "SFO", "New York"). destination: Destination airport code or city (e.g. "NRT", "LHR", "Paris"). departure_date: Departure date in YYYY-MM-DD format (e.g. "2025-03-15"). return_date: Optional return date in YYYY-MM-DD format for a round trip. In browse mode, round trips are searched as two one-way legs. num_passengers: Number of passengers. Defaults to 1. cabin_class: Optional cabin class preference. One of: "economy", "premium economy", "business", "first". mode: Leave as "browse" (default). "book" is a restricted alpha — only use it if the user explicitly asks to book a flight. page: 1-based results page, 10 options per page. Increment to see more options. airlines: Optional airline codes or names for browse mode (e.g. ["UA"] or ["United"]). Passed to the Google Flights search API. max_stops: Optional maximum stops per direction in browse mode. Use 0 for nonstop only, 1 for nonstop or one-stop itineraries. Returns: A ranked, paged list of flight options — airlines, routes, prices, and a link. Cash prices only. This tool does not currently return award (points/miles) pricing for flights, so do not state or imply a flight's points cost from these results. If the user asks how many miles a flight costs, say that award pricing is not available here right now and point them at the airline's own award search. Hotel award pricing is unaffected: the hotel tools still return points rates and cents-per-point.

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• search_hotels

  Search for hotels by location and dates with cash AND points pricing. Returns hotels with side-by-side cash vs points rates, cents-per-point (CPP) valuation, and deal scores so you can recommend the best value. This is Gondola's unique advantage — no other travel search shows both cash and points rates together. Args: location: City name, address, or area to search (e.g. "Tokyo", "Manhattan, New York", "near LAX airport"). checkin: Check-in date in YYYY-MM-DD format (e.g. "2026-04-15"). checkout: Check-out date in YYYY-MM-DD format (e.g. "2026-04-20"). num_adults: Number of adult guests. Defaults to 2. chain_name: Optional hotel chain to filter by (e.g. "marriott", "hilton", "hyatt", "ihg"). Case-insensitive substring match against each result's chain. If nothing matches, the unfiltered results are returned with an explicit note so you don't keep retrying. loyalty_programs: Optional list of the user's loyalty programs (e.g. ["hilton_honors", "marriott_bonvoy"]). When provided, results include personalized earnings and tier benefits like 5th night free. loyalty_points: Optional dict of program name to points balance (e.g. {"hilton_honors": 250000}). When provided, results indicate whether the user can afford each hotel with points. limit: Max number of hotels to return (default 20). The response notes how many more exist and how to narrow; raise this only when the user explicitly wants a longer list. Returns: Formatted list of hotels with cash rates, points rates, CPP valuation, and deal recommendations.

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• search_vehicles

  Search for rental vehicles at an airport or city. Args: pickup_location: Airport IATA code (e.g. "LAX", "JFK", "SFO"). pickup_datetime: Pickup date and time in ISO format (e.g. "2025-03-15T10:00:00"). dropoff_datetime: Drop-off date and time in ISO format (e.g. "2025-03-20T10:00:00"). vehicle_class: Optional preference: Economy, Compact, Standard, FullSize, Premium, Luxury, SUV, Van. Returns: List of available rental vehicles with rates and details.

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• update_traveler_profile

  Save a learned travel preference or experience to the user's traveler profile. Use when the user shares a durable preference, like, dislike, or trip experience that should inform future recommendations — "Always takes a window seat", "Prefers boutique hotels over chains", "Vegetarian". Don't save temporary logistics like "my flight lands at 3pm". Saved entries come back from get_traveler_context in later sessions, which is how a preference stated once is still known next time. Requires a Gondola account (API key). Args: profile_entry: The preference or experience to save. Be specific and actionable. Good: "Prefers ocean-view rooms". Bad: "Liked the hotel". Returns: Confirmation of the saved entry, or an error message.

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