Airbnb

You run an MCP server that enables AI assistants to search, analyze, and reason about Airbnb listings through natural language and voice interactions. It exposes a set of tools you can invoke from MCP clients, handles requests, and talks to the Airbnb data source to return structured results ready to present to users.

How to use

You use an MCP client (such as Claude Desktop or Cursor) to talk to the Airbnb MCP Server. Start by launching the MCP client and selecting the Airbnb MCP Server as your active endpoint. You can ask for listing searches, price analyses across date ranges, budget calculations, or side‑by‑side comparisons. The server orchestrates requests to specialized tools, processes the results, and returns structured data that your client can render as listings, charts, or summaries. If you begin with a broad request, you can refine it by specifying location, dates, guests, and price ranges. Voice-enabled flows route through a LiveKit voice agent where available, returning natural language or structured data depending on your client’s capabilities.

How to install

Prerequisites: Python 3.10 or higher, Git, and a RapidAPI key for Airbnb data.

Step 1 Create the working directory by cloning the project and entering the directory.

Step 2 Create and activate a virtual environment, then install dependencies.

Step 3 Create a configuration file containing your RapidAPI key to authorize API calls.

Step 4 Run the MCP server. The server starts in stdio mode, ready to accept MCP client connections.

git clone https://github.com/vedantparmar12/airbnb-mcp.git
cd airbnb-mcp

# Create and activate a virtual environment (example for macOS/Linux)
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r mcp-server-airbnb/requirements.txt

# Configure environment
cat > mcp-server-airbnb/.env << 'ENV'
RAPIDAPI_KEY=your_rapidapi_key_here
ENV

# Run the MCP server (stdio transport)
python mcp-server-airbnb/server.py

Configuration and runtime notes

Environment variables are required for API access. The server reads RAPIDAPI_KEY from a .env file placed in the mcp-server-airbnb directory. When you run the server, it registers a set of tools and awaits MCP client connections. You can adjust client configurations to point to this server and, if needed, provide additional environment variables for other integrations.

Troubleshooting and tips

Common issues include missing Python path or an unavailable RapidAPI key. Ensure you activate your virtual environment before starting the server and verify that RAPIDAPI_KEY is correctly set in the environment file. If the server fails to register tools, re-check the dependencies and ensure you are running the server from the expected directory.

Notes on tools and capabilities

The Airbnb MCP Server exposes a suite of tools for listing search, details, price analysis, trip budgeting, and comparison tasks. You interact with these tools through your MCP client as you formulate requests that specify parameters like location, dates, guests, and price constraints. The server handles validation, calls to the Airbnb data source, and structured formatting of results.

Additional setup references

If you are integrating with voice agents, you can extend the environment with LiveKit support and related plugins for enhanced speech processing. Ensure your OPENAI and Deepgram keys (if using OpenAI or Deepgram integrations) are configured in your environment when you enable voice-enabled workflows.

Available tools

airbnb_search

Basic search for listings by location, dates, and guests with optional filters like price limits and limit on results.

airbnb_listing_details

Retrieve detailed information for a specific listing by its ID, with optional guest and date parameters.

airbnb_price_analyzer

Compare listing prices across multiple date ranges to help identify the cheapest periods.

airbnb_trip_budget

Calculate the total cost of a trip, including accommodation, service fees, and taxes for a given date range and party size.

airbnb_compare_listings

Show side-by-side comparisons for 2–5 listings, including price, rating, and features.

airbnb_smart_filter

Apply advanced filters and sorting to refine search results by rating, amenities, and value.