Scrape Airbnb Listings with Pagination & Store in Google Sheets

This n8n workflow scrapes Airbnb listings for a specified location like London, using check-in/out dates and guest count. It handles pagination to collect data across multiple pages (up to a set limit), extracts core details such as names, prices, ratings, reviews, and URLs, then enhances with deeper info including house rules, highlights, descriptions, and amenities. All data is organized and appended to a Google Sheet for structured storage.

The workflow uses an MCP (Model Context Protocol) client for Airbnb tools (airbnb_search and airbnb_listing_details), making it compatible only with self-hosted n8n instances with community nodes. It features a loop for pagination until no more results or page limit reached, ensuring comprehensive data collection without manual intervention.

Benefits include time-saving automation for travel market research, competitive analysis, or pricing intelligence. Use cases: real estate investors tracking rental trends, travel agencies comparing accommodations, or data analysts building datasets for AI models. Saves hours of manual scraping and provides clean, exportable data.

Setup requires Google Sheets OAuth2 credentials, a pre-configured sheet with specific headers (id, name, url, etc.), and Airbnb MCP client setup. Ideal for users needing scalable accommodation data pipelines.