Bluemoonkey / Community / Price Hunter

Price Hunter App Blueprint

A complete architecture for a price tracking app — monitor competitor prices, compare across retailers, get alerts when prices drop, and visualize historical price trends. 12 nodes, ready to export to Cursor or Claude Code.

SaaS Automation 12 nodes
Table of contents
  1. What this app does
  2. Architecture diagram
  3. Node breakdown
  4. How it works end-to-end
  5. Cursor export prompt
  6. FAQ

What this app does

Price Hunter is for dropshippers, e-commerce sellers, and bargain hunters who need to track product prices across multiple retailers. Instead of manually checking Amazon, eBay, and competitor stores every day, the app scrapes prices on a schedule, stores historical data for trend analysis, compares prices across sources, and sends alerts when a price drops below a threshold or a competitor undercuts you.

This blueprint maps out 12 nodes across frontend pages, backend APIs, AI analysis, schedulers, a database, and an alert system. It's designed for a solo seller or small e-commerce team tracking 50-500 products.

Architecture diagram

Product Dashboard (Page)Price Alert Settings (Page)Add Product (Page)
↕
Products APIPrices APIAlerts API
↕
Price Comparison AI (AI)
↕
Price DB (PostgreSQL)Price Scraper (Cron)Alert Checker (Cron)

Node breakdown

Frontend pages

Backend APIs

AI prompt

Database & services

How it works end-to-end

  1. User opens Add Product and pastes an Amazon product URL
  2. The Price Scraper extracts product name, current price, and image
  3. Product appears on the Product Dashboard with its first price data point
  4. User opens Price Alert Settings and sets: "Alert me when price drops below $25"
  5. Every hour, the Price Scraper fetches the product page and stores the new price in Price DB
  6. Every 15 minutes, the Alert Checker compares latest prices against thresholds
  7. When price drops below $25, the Alert Checker triggers the alert and sends an email
  8. User opens the Product Dashboard, sees the price drop on the historical chart
  9. The Price Comparison AI analyzes prices across sources and recommends "buy now" or "wait"
  10. Alert appears in the triggered alerts list on the dashboard

The Price Scraper must respect robots.txt and rate limits. Aggressive scraping will get you blocked. This blueprint uses rotating user agents and exponential backoff, but you should also respect each retailer's terms of service and consider using official APIs where available (Amazon Product Advertising API, eBay Browse API).

Cursor export prompt

Open this blueprint in Bluemoonkey and export it, or copy the prompt below:

Ready to paste 
Build this app exactly as described.
Start with database schema and auth, then APIs, then frontend pages.

## Product Dashboard (Frontend Page)
List of tracked products with current price, lowest price, trend (up/down/stable),
and source. Click product for historical price chart. Sort by biggest drop or increase.

## Price Alert Settings (Frontend Page)
Configure alerts per product: "notify when price drops below X" or
"when competitor price is lower by Y%." Choose email or push. Set quiet hours.

## Add Product (Frontend Page)
Paste product URL from Amazon, eBay, or competitor store.
Scraper extracts product name, current price, and image.
Assign category and set alert threshold.

## Products API (REST Endpoint)
- GET /api/products — list with current price and trend
- POST /api/products — add from URL
- GET /api/products/:id/prices — historical price data for charts
- DELETE /api/products/:id — remove tracked product

## Prices API (REST Endpoint)
- GET /api/prices/latest — latest prices across all products and sources
- POST /api/prices — internal: scraper writes new price data
- GET /api/prices/compare/:productId — comparison across sources

## Alerts API (REST Endpoint)
- GET /api/alerts — list user's alert configurations
- POST /api/alerts — create alert rule
- PATCH /api/alerts/:id — edit threshold or notification preference
- GET /api/alerts/triggered — recently triggered alerts

## Price DB (PostgreSQL)
- products: id, user_id, name, url, image_url, category, user_selling_price, created_at
- price_history: id, product_id, source, price, currency, scraped_at
- alerts: id, product_id, type, threshold, notification_method, is_active, last_triggered
- users: id, email, created_at

## Price Comparison AI (AI Prompt)
Input: product name, prices from multiple sources, user's selling price
Task: analyze cheapest source, calculate price gaps as percentages,
flag significant changes (>5% drop or increase)
Output: structured comparison with cheapest source, price gap, and
trend recommendation ("buy now" or "wait — price trending down")

## Price Scraper (Cron Job)
Runs hourly. Fetches each tracked product page from each source.
Extracts current price, writes to price_history.
Rotating user agents. Retries failed scrapes with exponential backoff.
Respect robots.txt and rate limits.

## Alert Checker (Cron Job)
Runs every 15 minutes. Compares latest prices against alert thresholds.
If price crosses threshold, triggers alert and sends notification
via configured channel (email or push).

For more prompt templates, see our Cursor prompt template or Claude Code prompt template. New to planning? Read how to plan an app before coding.

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FAQ

What is a price tracking app?

A price tracking app monitors product prices across retailers, stores historical price data, compares competitors, and sends alerts when prices drop or competitors change their pricing. It helps dropshippers and e-commerce sellers stay competitive without manually checking prices.

Can I export this blueprint to Claude Code?

Yes. Open this blueprint in Bluemoonkey's free canvas and export it as a structured prompt. Paste it into Claude Code's CLI, add "Build this app exactly as described," and it generates the full project.

How does the price scraper work?

The scraper runs as a cron job every hour. It fetches each tracked product's page, extracts the current price using CSS selectors or regex patterns, and writes the data to the price_history table. It uses rotating user agents and exponential backoff to avoid getting blocked.

Is web scraping legal?

Web scraping is legal in many jurisdictions but must respect robots.txt, terms of service, and rate limits. This blueprint includes rate limiting and backoff, but you should review each retailer's terms and consider using official APIs (Amazon Product Advertising API, eBay Browse API) where available.