Newegg Product Scraper — prices, ratings & specs

Disclaimer: Unofficial tool — not affiliated with, sponsored by, or endorsed by Newegg. Data is read from a public product-search endpoint. No login. You are responsible for complying with applicable law and the site’s terms. No warranty on accuracy or availability. Provided for informational and research use.

PC parts catalog — keyword search rows with price, rating, review count, and short specs. Pair with Amazon Search or Walmart when you need the same SKU on another retailer.

Newegg catalog	Amazon search	Walmart catalog
Newegg Product Scraper ◄── you are here	Amazon Search Scraper	Walmart Scraper
Price, rating, specs, item number	Keyword SERP, ASIN, badges	ZIP-local price and stock

Also see: Flipkart Scraper · Amazon Today's Deals Scraper

This Newegg scraper turns a keyword into a structured Apify dataset: price, rating, review count, spec lines, item number, and image. Use it as a Newegg API alternative from Python, Node.js, or an MCP assistant. HTTP only, no browser.

---

When to use this Actor

• Newegg product scrape by the same keywords shoppers type into search
• PC parts price checks — GPUs, CPUs, RAM, SSDs, laptops, monitors
• Sort and price band — lowest price, best selling, rating, or a min/max USD filter
• Catalog fills that need item number, title, and a product URL in one row

When not to use this Actor

• Checkout, cart, or account automation
• Full review text — the row has rating and review count, not review bodies
• Seller contact data — no emails or phone numbers
• Amazon or Walmart prices — use Amazon Search Scraper or Walmart Scraper

---

Key features

• Keyword search — one or more queries in a single run
• Sort — featured, price, rating, reviews, best selling, release date
• Price filter — optional minimum and maximum USD
• Spec lines — the short bullets shown on the search card
• Deduped item numbers — the same product is stored once across keywords

---

Input

Field	Required	Default	Description
keywords	Yes	—	Search terms
sort	No	featured	Result order
minPrice / maxPrice	No	empty	USD price band
maxItems	No	30	Unique products to keep (1–300)
maxPages	No	1	Pages per keyword (about 30 products each)
proxyConfiguration	No	off	Leave off unless a run is blocked

{
  "keywords": ["RTX 5070", "Ryzen 7 9800X3D"],
  "sort": "lowest_price",
  "maxItems": 30,
  "maxPages": 1
}

---

Output

Each dataset row is one product card.

Field	Description
query	Keyword that returned the row
itemNumber	Newegg item number
title	Product title
price	Current price
currency	ISO currency
rating	Average rating
reviewCount	Number of reviews
priceSavePercent	Discount percent when the card shows one
plusPrice	Plus-member price when present
bullets	Short spec lines
imageUrl	Primary image
url	Product page
scrapedAt	ISO-8601 timestamp

{
  "source": "newegg",
  "query": "RTX 5070",
  "itemNumber": "14-137-933",
  "title": "MSI Ventus GeForce RTX 5070 Ti 16GB",
  "price": 1179.99,
  "currency": "USD",
  "rating": 4.6,
  "reviewCount": 396,
  "bullets": ["16GB 256-Bit GDDR7", "Boost Clock 2482 MHz"],
  "url": "https://www.newegg.com/p/14-137-933"
}

---

Use cases

• GPU and CPU price checks before a build or a restock
• Assortment research — which cards rank, how many reviews they have, and the short spec line
• Multi-retailer comps — take itemNumber and title, then price the same product with Amazon Search or Walmart
• Scheduled keyword runs — re-run the same input when you want a fresh price list

---

Integration examples

Replace YOUR_TOKEN with an Apify API token. The Actor stays private until you publish it.

Node.js

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_TOKEN" });
const run = await client.actor("crawloop/newegg-product-scraper").call({
  keywords: ["RTX 5070"],
  sort: "lowest_price",
  maxItems: 20,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("crawloop/newegg-product-scraper").call(run_input={
    "keywords": ["RTX 5070"],
    "sort": "lowest_price",
    "maxItems": 20,
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

cURL

curl "https://api.apify.com/v2/acts/crawloop~newegg-product-scraper/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords":["RTX 5070"],"sort":"lowest_price","maxItems":20}'

---

MCP and AI assistants

Use this Actor from AI tools via Apify MCP. Connect your Apify account, then call this Actor by name.

Example prompts:

• "Run Newegg Product Scraper for RTX 5070, sort by lowest price, and return the top 20 rows as JSON."
• "Scrape Ryzen 7 9800X3D on Newegg and summarize price, rating, and spec lines."
• "Chain Newegg Product Scraper then Amazon Search Scraper and compare titles and prices."

---

Suite next step

After a Newegg price list, run Amazon Search Scraper on the same product titles for a second retail price. For a US big-box check, use Walmart Scraper with a ZIP.

---

FAQ

Is this a browser scrape?
No. One HTTP call per search page. Default memory is 256 MB. Leave proxy off.

Does an empty keyword list still finish?
Yes. With no keywords the run stores zero rows and exits.

Can I get review text or seller emails?
No. Rows include rating and review count only.

How many products are on a page?
About 30. Raise maxPages and maxItems together if you need more than the first page.