Airbnb MCP Server Integration

What does “Airbnb” MCP Server do?

The Airbnb MCP (Model Context Protocol) Server enables AI assistants to search Airbnb for listings and retrieve detailed information about specific accommodations. By acting as an intermediary, it empowers development workflows with real-time access to Airbnb’s publicly available data, facilitating tasks like searching for properties by location, filtering by dates and guest counts, and extracting granular listing details such as prices, amenities, and host information. This server returns structured JSON data, streamlining the integration of Airbnb search and discovery features into applications or AI agents without requiring an API key. The Airbnb MCP Server is particularly useful for developers building travel-planning tools, recommendation systems, or travel assistant bots that need programmatic access to up-to-date Airbnb listings.

List of Prompts

No explicit prompt templates are mentioned in the available documentation or code.

List of Resources

No explicit MCP resources (for LLM context) are mentioned in the available documentation or code.

List of Tools

• airbnb_search
  Search for Airbnb listings.

  • Required input: location (string)
  • Optional inputs: placeId, checkin, checkout, adults, children, infants, pets, minPrice, maxPrice, cursor, ignoreRobotsText
  • Returns: Array of listings with details like name, price, location, etc.

• airbnb_listing_details
  Get detailed information about a specific Airbnb listing.

  • Required input: id (string)
  • Optional inputs: checkin, checkout, adults, children, infants, pets, ignoreRobotsText
  • Returns: Detailed listing information including description, host details, amenities, pricing, etc.

Use Cases of this MCP Server

• Travel Planning Bots
  Enable AI agents to fetch up-to-date Airbnb listings for specific locations and dates, allowing users to plan vacations or business trips efficiently.

• Accommodation Recommendation Systems
  Integrate Airbnb search and property detail retrieval into recommendation engines to help users find suitable stays based on personal preferences and filters.

• Price Comparison Tools
  Use the structured data returned from Airbnb searches to compare prices and amenities across different listings, aiding users in finding the best value.

• Market Research & Analytics
  Gather and analyze Airbnb listing data at scale for market research, such as tracking trends in pricing, availability, or property types in various regions.

• Integration with Itinerary Builders
  Enhance itinerary management platforms by embedding real-time Airbnb search and booking information as part of a holistic travel planning experience.

How to set it up

Windsurf

No setup instructions or configuration details are provided for Windsurf in the documentation.

Claude

1. Ensure Node.js is installed on your machine.

2. Go to: Settings > Developer > Edit Config.

3. Add the following to your claude_desktop_config.json:

   {
     "mcpServers": {
       "airbnb": {
         "command": "npx",
         "args": [
           "-y",
           "@openbnb/mcp-server-airbnb"
         ]
       }
     }
   }
   

   To ignore robots.txt for all requests, use this version:

   {
     "mcpServers": {
       "airbnb": {
         "command": "npx",
         "args": [
           "-y",
           "@openbnb/mcp-server-airbnb",
           "--ignore-robots-txt"
         ]
       }
     }
   }
   

4. Restart Claude Desktop.

Securing API Keys

• No API key is required for this server.

Cursor

No setup instructions or configuration details are provided for Cursor in the documentation.

Cline

No setup instructions or configuration details are provided for Cline in the documentation.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "airbnb": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "airbnb" to whatever name you use for your MCP server and replace the URL with your own MCP server URL.

Overview

Based on the tables above, Airbnb MCP Server is straightforward and focused—with strong tooling but lacking in reusable prompt templates and explicit resource primitives. It’s easy to set up, requires no API key, and is well-documented for Claude Desktop, but lacks documented support for other platforms and for advanced MCP features like resources, roots, or sampling.

Our opinion

Given the available documentation, Airbnb MCP Server is highly practical for its travel and accommodation use case, but it does not expose advanced MCP concepts like roots, sampling, or resources, and supports only a narrow toolset. The lack of prompt templates and cross-platform instructions limits its flexibility, but it excels in simplicity and focus. We rate it a 6/10 for general MCP server completeness and developer utility.

MCP Score