Use casePrice comparison

Price comparison API. Every seller's price for one product.

Send one product, get back every seller that lists it: price, total with shipping, stock and delivery notes, and a direct link to each listing. 1 credit a product, from your agent or your code.

Updated · datawebot team

13 sellers, $159.99 to $399.99.

One read of the Sony WH-1000XM5 headphones in the US on 29 October 2026 at 02:21 UTC, sorted by total with shipping. BrandsMart USA lists $299.99, but its $100 delivery makes it one of the most expensive.

get_product · US · Sony WH-1000XM513 offers
SellerPriceShippingTotal
Secondipity$159.99Free$159.99
Sony$228.00Free$228.00
Greentoe$249.00Free$249.00
Walmart - TheRightOne$249.99Free$249.99
Best Buy marketplace seller$254.99Free$254.99
Macy's$298.00Free$298.00
Sweetwater$298.00Free$298.00
B&H Photo-Video-Audio$298.00Free$298.00
TikTok Shop$349.99Free$349.99
PC Richard & Son$399.95Free$399.95
Target$399.99Free$399.99
Verizon$399.99Free$399.99
BrandsMart USA$299.99+ $100.00$399.99

Prices are what each shop showed at that time, a dated snapshot rather than current prices. Each offer also carries a direct link, stock and delivery notes, and any discount the shop shows.

Two calls, then sort.

  1. Find the product. Search by name or model number. Each result has a product_id. 5 credits a search.
  2. Read every seller's offer. Read the product with that product_id. The answer lists each seller with price, total with shipping, stock and delivery notes, and a direct link. 1 credit.
  3. Compare totals, not prices. Sort by the total with shipping. A low list price with a high delivery charge can end up the most expensive.
  4. Check the match. Confirm each listing is the same product, color and condition before you call it the cheapest.

From your agent or your own code.

In an agent, ask in plain words and it calls search_products then get_product. In code, the same two reads go to POST /v1/requests with your API key.

API

In Python

compare_prices.py
import os
import time

import requests

API = "https://api.datawebot.com/v1/requests"
HEADERS = {"Authorization": f"Bearer {os.environ['DATAWEBOT_API_KEY']}"}


def ask(body):
    answer = requests.post(API, json=body, headers=HEADERS, timeout=120).json()
    while answer.get("status") == "working":  # finish a slow answer
        time.sleep(3)
        answer = requests.get(f"{API}/{answer['request_id']}", headers=HEADERS, timeout=120).json()
    return answer


def total(offer):
    text = offer.get("total_text") or offer["price"]["text"]
    return float(text.replace("$", "").replace(",", ""))


# 1. Find the product: 5 credits
found = ask({"capability": "search", "query": "Sony WH-1000XM5", "country": "US", "limit": 5})
product_id = found["products"][0]["product_id"]

# 2. Every seller's offer for it: 1 credit
product = ask({"capability": "product", "product_id": product_id})

# 3. Cheapest total first
for offer in sorted(product["offers"], key=total):
    print(f"{total(offer):>9.2f}  {offer['shop']:<32} {offer['url']}")
Every field a product read returns

A few useful answers.

What is a price comparison API?

An API that takes one product and returns the offers for it from many shops: who sells it, at what price, with what shipping, and a link to each listing. You use it to find the cheapest seller, watch competitors or check that resellers follow your pricing.

How many sellers come back?

As many as the shops show for that product when it is read. In the example on this page, one pair of headphones in the US returned 13 sellers, from the brand's own store to department stores and marketplace sellers.

Are the prices live?

Each read is what the shops showed at that moment, labelled with when it was read (meta.as_of). Prices move during the day, so treat a read as a dated snapshot and read again when you need a newer one.

Does it keep price history or send alerts?

No. Each read is one snapshot. To track prices over time, run the same read on a schedule and store the results in your own spreadsheet or database.

What does a comparison cost?

A search costs 5 credits and a product read with every seller's offer costs 1. Failed reads are free. Every account starts with 200 free credits.

Can my AI agent do this without code?

Yes. Connect the datawebot MCP server and ask who sells a product and for how much. The agent calls search_products, then get_product, and shows each seller with a link.