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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_hotelsA

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.
get_hotel_detailsA

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.
compare_ratesA

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.
get_booking_linkA

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.
get_rate_alertsA

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.
get_upcoming_tripsA

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.
get_past_tripsA

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.
get_loyalty_accountsA

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.
get_free_night_creditsA

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.
predict_priceA

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.
get_hotel_statsA

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.
get_multi_night_ratesA

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.
get_similar_hotelsA

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.
optimize_loyalty_portfolioA

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.
search_flightsA

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.
search_eventsB

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

search_vehiclesA

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.
get_vehicle_detailsA

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.
get_vehicle_bookingA

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.
get_vehicle_booking_linkA

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.
credit_card_coverageA

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.
get_vehicle_booking_coverageA

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.
get_hotel_reviewsA

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.
get_suggested_searchesA

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.
get_bookingA

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.
diagnose_ratesA

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.
get_travel_profilesA

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.
get_traveler_contextA

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.
update_traveler_profileA

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.
create_rate_alertA

Create a rate alert to monitor a hotel for price drops.

Set up an alert to be notified by email when the rate drops for a specific hotel.
Optionally specify dates, or leave them out to monitor any stay.
Requires a Gondola account with an API key.

Args:
    hotel_id: The hotel's Vervotech property ID (from search results).
    checkin: Check-in date in YYYY-MM-DD format. Must be provided with checkout, or both omitted.
    checkout: Check-out date in YYYY-MM-DD format. Must be provided with checkin, or both omitted.

Returns:
    Confirmation that the rate alert was created, with notification details.
delete_rate_alertA

Delete a rate alert so you stop monitoring a hotel for price drops.

Requires a Gondola account with an API key.

Args:
    alert_id: The rate alert ID to delete (from get_rate_alerts).

Returns:
    Confirmation that the rate alert was deleted.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.7/5.0

Scored across 31 tools

Disambiguation3/5

Most tools target distinct resources, but hotel analytics tools blur together: search_hotels already provides side-by-side cash/points comparison that compare_rates duplicates, and predict_price/get_hotel_stats both evaluate whether a current rate is good. Detailed descriptions help, but an agent could still select the wrong value-assessment tool.

Naming Consistency4/5

Names overwhelmingly follow a get_/search_/create_/delete_/update_ + noun pattern, which is predictable and consistent. Minor deviations like credit_card_coverage (missing verb) and the similar get_travel_profiles/get_traveler_context pair keep it from being perfect.

Tool Count2/5

At 31 tools, this exceeds the 25+ threshold for 'too many' and feels heavy even for a broad travel domain. Several hotel rate and value tools could be consolidated without losing capability.

Completeness3/5

The server covers hotel search/comparison/booking links, flights, vehicles, loyalty, trips, and traveler context well. Notable gaps exist: no booking cancellation/update, no flight award pricing (explicitly unsupported), and no event details beyond search, which creates some dead ends.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive