Build a hotel rate-parity watcher with Claude Desktop and SQLite

A developer published an open-source Google Hotels MCP server (huynhtanan/google-hotels-mcp) that connects Claude Desktop to hotel pricing data, paired with a roughly 20-line SQLite logger to track rate parity across OTAs. The setup calls search_hotels once per check-in date, storing hotel, date, OTA and price tuples in a snapshot table, then uses a window-function SQL query to surface the cheapest versus reference price and flag drift beyond a threshold. The author notes the server relies on three paid Apify actors, with Apify's free tier covering about 60 full-city searches per month.

Rate parity is the agreement every hotel signs with each OTA: no booking site can list the room cheaper than our website . In practice it breaks constantly — one site runs a flash discount, another forgets to resync a package rate. If you own a hotel, catching that drift in 24 hours instead of 10 days is money. This post wires the Google Hotels MCP server to a 20-line SQLite logger. Claude Desktop asks the question, the script writes the diff. You end up with a daily table like this: hotel date booking expedia agoda delta Ritz Paris 2026-11-15 €1,480 €1,520 €1,480 -2.6% Hotel Lutetia 2026-11-15 €820 €820 €795 -3.1% Mandarin Oriental Paris 2026-11-15 €1,650 €1,650 €1,650 0.0% Disclosure: the MCP server huynhtanan/google-hotels-mcp , open source calls three paid Apify actors I wrote. Apify's free tier ships $5 of credit per month — about 60 full-city searches — before you need to upgrade. No card required to sign up. Same install as the previous post https://dev.to/huynhtanan/add-google-hotels-to-claude-desktop-as-an-mcp-server-2-minute-setup-1m00 . Add this block to claude desktop config.json : { "mcpServers": { "google-hotels": { "command": "uvx", "args": "--from", "git+https://github.com/huynhtanan/google-hotels-mcp.git@v0.1.2", "google-hotels-mcp" , "env": { "APIFY TOKEN": "apify api ..." } } } } Restart Claude Desktop. Three tools appear: search hotels , hotel price calendar , search vacation rentals . python import sqlite3 db = sqlite3.connect "rate parity.db" db.executescript """ CREATE TABLE IF NOT EXISTS snapshot captured at TEXT NOT NULL, hotel TEXT NOT NULL, stay date TEXT NOT NULL, ota TEXT NOT NULL, price REAL NOT NULL, currency TEXT NOT NULL, PRIMARY KEY captured at, hotel, stay date, ota ; CREATE INDEX IF NOT EXISTS snapshot recent ON snapshot hotel, stay date, captured at DESC ; """ db.commit Keeping currency as a column instead of baking EUR into the field name means the same table can hold USD, GBP, or BRL snapshots when you expand beyond one region. "Snapshot the top 20 Paris hotels across the next 30 check-in dates: for each date, call search hotels with query="hotels in Paris" , include provider prices=true , max results=20 , two adults, EUR. Insert each hotel, stay date, ota, price tuple into the snapshot table in rate parity.db ." Claude issues one search hotels call per date 30 calls total , each returning ~20 hotels and their providers array. That's 30 × 20 = 600 hotel, date rows per snapshot. The whole thing runs in your Claude Desktop session — no external cron. Here is what the MCP tool actually returns for one hotel on one date lightly trimmed : { "name": "Hotel Lutetia", "checkIn": "2026-11-15", "checkOut": "2026-11-16", "providers": {"name": "Booking.com", "price": 820, "currency": "EUR"}, {"name": "Expedia", "price": 820, "currency": "EUR"}, {"name": "Agoda", "price": 795, "currency": "EUR"}, {"name": "Hotels.com", "price": 820, "currency": "EUR"} , "rating": 4.6, "reviewsCount": 2341 } Once snapshot rows exist, a single SQL query surfaces drift: WITH latest AS SELECT hotel, stay date, ota, price, currency, ROW NUMBER OVER PARTITION BY hotel, stay date, ota ORDER BY captured at DESC AS rn FROM snapshot , today AS SELECT FROM latest WHERE rn = 1 , agg AS SELECT hotel, stay date, currency, MIN price AS cheapest, MAX price AS reference, COUNT DISTINCT ota AS ota count FROM today GROUP BY hotel, stay date, currency HAVING ota count = 2 SELECT hotel, stay date, currency, cheapest, reference, ROUND cheapest - reference 100.0 / reference, 2 AS delta pct FROM agg WHERE cheapest - reference 100.0 / reference <= -3.0 ORDER BY delta pct ASC LIMIT 50; The ota count = 2 guard is important — a hotel with only one OTA listed is not a parity signal; it is just a single price point. Any row that comes back is a rate-parity violation at least 3% deep. Pipe it into Slack, email, or just a daily markdown digest. "Of today's drift rows, which 3 would cost the hotel the most if a corporate traveler booked 10 nights on the cheapest OTA instead of the reference OTA?" Claude runs the arithmetic directly against the drift rows and writes a one-paragraph summary. The whole feedback loop — scrape, diff, prioritize, explain — runs inside one chat window. search hotels pricing: $0.002/hotel + $0.002/provider-prices row → 600 × $0.004 ≈ examples/rate parity/ run 20 hotels × 7 nights = $0.56/day stays in the free tier for ~9 days a month The actor is pay-per-result — you pay only for rows that actually came back, not for failed runs or empty days. The MCP server, the SQLite schema, and the drift query are in huynhtanan/google-hotels-mcp https://github.com/huynhtanan/google-hotels-mcp under examples/rate parity/ . One-file CLI, no framework — the same script can also run from a cron, which is handy if you want nightly snapshots without keeping Claude Desktop open. If you have a single hotel and want to try this against your own property — ping me comments are open . I'm interested in which fields the parity teams actually care about so I can bake them into the next cut of the server.