ai-airbnb-search

Ersa-tech/ai-airbnb-search

3.1

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The Model Context Protocol (MCP) server is a specialized server designed to handle and process data for AI-powered applications, integrating seamlessly with various components to provide real-time data and services.

AI-Powered Airbnb Search Application

A comprehensive AI-powered Airbnb search application with natural language processing capabilities, built with React frontend, Flask backend, and MCP server integration.

🏗️ Architecture Overview

  • Frontend: React with TypeScript, mobile-first design
  • Backend: Flask API with OpenRouter LLM integration
  • MCP Server: Containerized Airbnb data service
  • Deployment: Render.com with GitHub CLI workflow

📁 Project Structure

ai-airbnb-search/
├── backend/                 # Flask API server
│   ├── services/           # Business logic services
│   ├── tests/              # Backend tests
│   ├── app.py              # Main Flask application
│   └── requirements.txt    # Python dependencies
├── frontend/               # React application
│   ├── src/
│   │   ├── components/     # React components
│   │   ├── services/       # API services
│   │   └── utils/          # Utility functions
│   ├── public/             # Static assets
│   └── package.json        # Node.js dependencies
├── mcp-server/             # MCP server implementation
│   ├── src/                # MCP server source
│   ├── tests/              # MCP server tests
│   ├── Dockerfile          # Container configuration
│   └── package.json        # Node.js dependencies
├── docs/                   # Documentation
├── scripts/                # Build and deployment scripts
└── render.yaml             # Render.com deployment config

🚀 Features

  • Natural Language Search: AI-powered search using OpenRouter LLM
  • Mobile-First Design: Optimized for mobile devices with touch gestures
  • Property Carousel: Displays exactly 5 properties with swipe navigation
  • Real-time Data: Live Airbnb property data via MCP server
  • Responsive UI: Works seamlessly across all device sizes

🛠️ Technology Stack

Frontend

  • React 18 with TypeScript
  • Tailwind CSS for styling
  • React Query for state management
  • Lucide React for icons

Backend

  • Flask with Python 3.11+
  • OpenRouter API integration
  • Gunicorn for production
  • Comprehensive error handling

MCP Server

  • Node.js with TypeScript
  • Docker containerization
  • HTTP wrapper for API access
  • Airbnb data integration

🔧 Development Setup

Prerequisites

  • Node.js 18+
  • Python 3.11+
  • Docker
  • GitHub CLI

Installation

  1. Clone the repository

    git clone https://github.com/Ersa-tech/ai-airbnb-search.git
cd ai-airbnb-search

  2. Backend Setup

    cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
python app.py

  3. Frontend Setup

    cd frontend
npm install
npm start

  4. MCP Server Setup

    cd mcp-server
npm install
npm run build
docker build -t ai-airbnb-mcp .
docker run -p 8080:8080 ai-airbnb-mcp

🌐 Deployment

The application is configured for deployment on Render.com with three services:

  1. MCP Server: Docker service
  2. Backend: Web service (Flask)
  3. Frontend: Static site (React)

Deploy using the provided render.yaml configuration.

📱 Mobile Optimization

  • Touch targets minimum 44px
  • Swipe gestures for carousel
  • Progressive enhancement
  • Dark mode support
  • Optimized for 320px+ screens

🔐 Security

Configured for internal use with simplified security:

  • CORS disabled for internal access
  • Environment-based configuration
  • Secure API key management

📊 Performance

  • Lazy loading for images
  • Optimized bundle sizes
  • Efficient API caching
  • Mobile-first loading strategies

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Test thoroughly
  5. Submit a pull request

📄 License

This project is for internal use only.

🆘 Support

For issues and questions, please refer to the documentation in the docs/ directory.