Big Watermelon Daily Deals MCP Server

An MCP (Model Context Protocol) server that automatically fetches and analyzes daily produce deals from Big Watermelon, a fruit and vegetable wholesale store in Melbourne, Australia. The server uses Requesty.ai to extract deal information from images and makes it available to AI agents via the MCP protocol.

Features

• Automated Daily Fetching: Retrieves deals once per day after 7 AM Australia/Melbourne time
• AI-Powered Extraction: Uses Requesty.ai to analyze deal images and extract structured data
• Intelligent Caching: 24-hour cache to minimize API calls and improve performance
• Production-Ready: Includes rate limiting, graceful shutdown, comprehensive logging, and error handling
• Highly Configurable: All settings configurable via environment variables
• Performance Optimized: Concurrent processing with exponential backoff retry logic
• SSE Transport: Server-Sent Events for real-time MCP communication

Architecture

graph TB
    subgraph "MCP Clients"
        A[Cline/Roo Code]
        B[Claude Desktop]
        C[AnythingLLM]
    end
    
    subgraph "MCP Server"
        D[SSE Transport]
        E[Rate Limiter]
        F[MCP Handler]
    end
    
    subgraph "Core Logic"
        G[Deals Fetcher]
        H[Cache Manager]
        I[Image Processor]
    end
    
    subgraph "External Services"
        J[Big Watermelon Website]
        K[Requesty.ai API]
    end
    
    A --> D
    B --> D
    C --> D
    D --> E
    E --> F
    F --> G
    G --> H
    H --> I
    I --> J
    I --> K
    
    style D fill:#e1f5ff
    style G fill:#fff4e1
    style K fill:#ffe1e1

Requirements

• Go: 1.24.3 or later
• Requesty.ai API Key: Required for image analysis
• Optional: Docker for containerized deployment

Installation

Local Setup

1. Clone the repository:

   git clone https://github.com/hebra/ahemseepee/daily-deals-mcp-server.git
   cd daily-deals-mcp-server
   

2. Set up environment variables:

   export REQUESTY_API_KEY=your-requesty-api-key-here
   

3. Install dependencies:

   make deps
   

4. Build and run:

   make build
   make run
   

The server will start on http://localhost:8080 with the following endpoints:

• GET /sse - SSE connection endpoint for MCP clients
• POST /message - MCP message endpoint
• GET /health - Health check endpoint
• GET /ready - Readiness check endpoint

Docker Setup

# Build Docker image
make docker-build

# Run Docker container
make docker-run

Configuration

All configuration is done via environment variables with sensible defaults:

Required Configuration

| Variable | Description | Default | |----------|-------------|---------| | REQUESTY_API_KEY | Requesty.ai API key for image analysis | (Required) |

Requesty.ai Configuration

| Variable | Description | Default | |----------|-------------|---------| | REQUESTY_BASE_URL | Requesty.ai API base URL | https://router.requesty.ai/v1 | | REQUESTY_MODEL | AI model to use | google/gemini-2.5-flash | | REQUESTY_MAX_TOKENS | Maximum tokens in response | 4096 | | REQUESTY_TEMPERATURE | Model temperature (0.0-1.0) | 0.0 |

Server Configuration

| Variable | Description | Default | |----------|-------------|---------| | PORT | HTTP server port | 8080 | | RATE_LIMIT_REQUESTS | Maximum requests per window | 100 | | RATE_LIMIT_WINDOW | Rate limit time window | 1m |

Fetching Configuration

| Variable | Description | Default | |----------|-------------|---------| | FETCH_HOUR | Hour to fetch deals (0-23, Melbourne time) | 7 | | CACHE_FILE | Path to cache file | bigwatermelon-dailydeals.cached.json | | SPECIALS_URL | URL to scrape for deals | https://www.bigwatermelon.com.au/category/specials/ | | TIMEZONE | Timezone for scheduling | `Australia/Mel

... View full README on GitHub