Search and explore Airbnb listings with advanced filters—retrieve detailed property info via a fast MCP server interface
Fetch and extract information from websites automatically
Example: Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example: Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example: Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Interact with services that don't offer APIs
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Automate interactions with any website, even without API
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Airbnb Search & Listings is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We wired Airbnb Search & Listings into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Airbnb Search & Listings reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Airbnb Search & Listings is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Airbnb Search & Listings against two servers with overlapping tools; this profile had the clearer scope statement.
Useful MCP listing: Airbnb Search & Listings is the kind of server we cite when onboarding engineers to host + tool permissions.
Airbnb Search & Listings is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Airbnb Search & Listings surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Airbnb Search & Listings has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Airbnb Search & Listings is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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Claude Desktop configuration
{
"mcpServers": {
"airbnb": {
"command": "npx",
"args": [
"-y",
"@openbnb/mcp-server-airbnb"
]
}
}
}Search Airbnb listings with advanced filters and retrieve detailed property information including direct booking links.
You can install Airbnb Search & Listings in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
A comprehensive Desktop Extension for searching Airbnb listings with advanced filtering capabilities and detailed property information retrieval. Built as a Model Context Protocol (MCP) server packaged in the Desktop Extension (DXT) format for easy installation and use with compatible AI applications.
This extension is packaged as a Desktop Extension (DXT) file. To install:
.dxt file from the releases pageBefore starting make sure Node.js is installed on your desktop for npx to work.
Go to: Cursor Settings > Tools & Integrations > New MCP Server
Add one the following to your mcp.json:
{
"mcpServers": {
"airbnb": {
"command": "npx",
"args": [
"-y",
"@openbnb/mcp-server-airbnb"
]
}
}
}
To ignore robots.txt for all requests, use this version with --ignore-robots-txt args
{
"mcpServers": {
"airbnb": {
"command": "npx",
"args": [
"-y",
"@openbnb/mcp-server-airbnb",
"--ignore-robots-txt"
]
}
}
}
Restart.
The extension provides the following user-configurable options:
falseairbnb_searchSearch for Airbnb listings with comprehensive filtering options.
Parameters:
location (required): Location to search (e.g., "San Francisco, CA")placeId (optional): Google Maps Place ID (overrides location)checkin (optional): Check-in date in YYYY-MM-DD formatcheckout (optional): Check-out date in YYYY-MM-DD formatadults (optional): Number of adults (default: 1)children (optional): Number of children (default: 0)infants (optional): Number of infants (default: 0)pets (optional): Number of pets (default: 0)minPrice (optional): Minimum price per nightmaxPrice (optional): Maximum price per nightcursor (optional): Pagination cursor for browsing resultsignoreRobotsText (optional): Override robots.txt for this requestReturns:
airbnb_listing_detailsGet detailed information about a specific Airbnb listing.
Parameters:
id (required): Airbnb listing IDcheckin (optional): Check-in date in YYYY-MM-DD formatcheckout (optional): Check-out date in YYYY-MM-DD formatadults (optional): Number of adults (default: 1)children (optional): Number of children (default: 0)infants (optional): Number of infants (default: 0)pets (optional): Number of pets (default: 0)ignoreRobotsText (optional): Override robots.txt for this requestReturns:
# Install dependencies
npm install
# Build the project
npm run build
# Watch for changes during development
npm run watch
The extension can be tested by running the MCP server directly:
# Run with robots.txt compliance (default)
node dist/index.js
# Run with robots.txt ignored (for testing)
node dist/index.js --ignore-robots-txt
MIT License - see LICENSE file for details.
Contributions are welcome! Please read the contributing guidelines and submit pull requests for any improvements.
Note: This extension is not affiliated with Airbnb, Inc. It is an independent tool designed to help users search and analyze publicly available Airbnb listings.
Time estimate: 20-40 minutes including configuration and testing
Prerequisites
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.