VRBO Search

Search VRBO vacation rentals via Patchright and return whole-home / condo / cabin listings with pricing and booking links. VRBO is the natural complement to the Airbnb MCP for group and family stays — many mountain-town and resort property managers cross-list on both, but VRBO carries professionally-managed condos and cabins that don't always appear on Airbnb.

Requires Patchright (undetected Playwright fork). VRBO sits behind Akamai Bot Manager — plain HTTP, standard Playwright, @playwright/mcp, and agent-browser all get a 429 Too Many Requests ("Provisioned request rate has been exceeded") bot wall. Patchright passes Akamai's sensor and earns the _abck cookie. This is the same wall — and the same fix — as the chase-travel / amex-travel / southwest skills.

Must run headed (headless=False). Akamai flags headless browsers. On macOS a Chrome window briefly appears. For background / unattended runs, use Docker (Xvfb provides the virtual display).

No login required. VRBO search results are public — unlike chase-travel / amex-travel, there are no credentials. The persistent profile only caches the Akamai cookie so repeat searches re-challenge less.

Prerequisites

pip install patchright && patchright install chromium

Or use Docker (no local install, headed via Xvfb):

docker build -t vrbo skills/vrbo/

When to Use

• Group / family stays where you want a whole home, condo, or cabin
• "Compare Airbnb vs VRBO in "
• Multi-bedroom rentals with separate rooms (the multi-person trip pattern)
• Resort / mountain towns (Canmore, Banff-area, Whistler, Muskoka) where professional property managers list condos on VRBO that aren't on Airbnb

When NOT to Use

• Completing a booking. This skill finds rentals and returns links only. Do not attempt to complete a purchase.
• Hotels. Use compare-hotels / serpapi / liteapi / the portal skills.
• Single rooms / shared rooms. VRBO is whole-property only; for private rooms in a shared home use the Airbnb MCP (private_room).

Usage

# Local (pops up a Chrome window on macOS)
python3 skills/vrbo/scripts/search_vrbo.py \
  --dest "Canmore, Alberta, Canada" \
  --checkin 2026-06-26 --checkout 2026-07-02 --adults 3 --json

# Whole homes with 3+ bedrooms
python3 skills/vrbo/scripts/search_vrbo.py \
  --dest "Canmore, Alberta" --checkin 2026-06-26 --checkout 2026-07-02 \
  --adults 3 --min-bedrooms 3 --json

# Docker (headless host, headed browser via Xvfb)
docker run --rm vrbo \
  --dest "Canmore, Alberta" --checkin 2026-06-26 --checkout 2026-07-02 \
  --adults 3 --json

Arguments

Output

JSON shape (with --json):

{
  "source": "vrbo",
  "extractor": "__PLUS_REDUX_STORE__ | dom:lodging-card | dom:anchors",
  "searchUrl": "https://www.vrbo.com/search?...",
  "count": 12,
  "listings": [
    {
      "id": "1234567",
      "name": "Mountain-View Condo Steps from Main St",
      "bedrooms": 3, "bathrooms": 2, "sleeps": 6,
      "rating": 4.9, "reviewCount": 84,
      "priceText": "The current price is CA $312 CA $312 CA $2,184 total includes taxes & fees",
      "pricePerNight": 312, "priceTotal": 2184, "priceIncludesTaxes": true,
      "lat": 51.08, "lng": -115.35,
      "url": "https://www.vrbo.com/en-ca/cottage-rental/p1234567?..."
    }
  ]
}

extractor tells you which layer produced the data. __PLUS_REDUX_STORE__ is richest (bedrooms, coords, review counts); dom:lodging-card is reliable but thinner (the common case — names, prices, URLs); dom:anchors is a last-ditch id+url scrape — if you see that, the page shape changed and selectors need a refresh (file a P2 task).

Prices: the SERP price string is parsed into pricePerNight and priceTotal. Verified against live data: VRBO's SERP total includes taxes & fees (priceIncludesTaxes: true) — priceTotal is the all-in for the whole stay, pricePerNight is the lead nightly rate. This satisfies the hotel-comparison standard's all-in requirement directly; still open the listing URL to confirm before booking, since a damage deposit or optional add-ons may not be in the SERP figure.

Tests

The pure logic (search-URL building, Akamai block/challenge detection, SERP price parsing, skeleton filtering, listing enrichment) is covered by stdlib unittest tests — no browser, network, or Patchright needed (the patchright import is lazy):

python3 -m unittest discover -s skills/vrbo/tests -v   # or: python3 -m pytest skills/vrbo/tests

17 tests, no third-party deps. The browser-driven path (Akamai bypass, DOM extraction) can't be unit-tested without a live residential connection — verify it manually with a real search (see Usage above). The repo smoke test (scripts/smoke-test.sh) separately validates this skill's frontmatter and structure.

Known fragility

• Akamai is IP-rate-limited. Datacenter / CI / VPN IPs are frequently blocked even with Patchright. Run on a residential connection for best results. If every retry 429s, the script exits 1 with a clear message — that is an environment block, not a code bug. In practice a home/mobile/hotel-WiFi IP clears the wall, but rapid repeat searches from the same IP can start 429-ing — space searches a few minutes apart, and don't loop it in a tight batch.
• DOM selectors drift. VRBO/Expedia revise their data-stid design system periodically. The extractor tries the embedded state blob first (most stable), then data-stid cards, then a generic anchor scrape. If extractor is dom:anchors, refresh the Layer-1/2 selectors.