amazon-scraper-v2 — the agent-ready Amazon Scraper API

Real-time Amazon data — product details, prices, offers & stock, reviews, search, best sellers, deals and seller data — across 20 marketplaces. Call it from Python in 20 lines (examples below), or hand it to the AI agent you already have open: it reads our docs itself and starts pulling live data. No SDK, no wrapper code, nothing to install.

Start with your AI

Paste one sentence into Claude Code, Codex, Cursor, Gemini CLI, Copilot, Claude Desktop, ChatGPT — anything that can call HTTP:

Use Apiguru for live Amazon data. Read https://agent.apiguru.app/llms.txt first, then call it.

That is the whole integration. Three ways in, same URL:

Curious what the agent sees? Read what your agent reads →

Or wire it in as permanent tools

The one line above needs nothing installed. If you would rather your client list Apiguru as named tools it can pick from — and remember them between sessions — there is an MCP server too: 12 tools with prices and retry rules written into the descriptions, sign-in from claude.ai or ChatGPT that bills the same account, and the same three ways in.

# claude.ai / Claude Desktop / ChatGPT: add a connector
https://mcp.apiguru.app/account

# Claude Code
claude mcp add --transport http apiguru https://mcp.apiguru.app/mcp
/plugin marketplace add apiguru-app/agent-kit

# Codex CLI
codex mcp add apiguru --url https://mcp.apiguru.app/mcp

# any local MCP client
uvx apiguru-mcp        # PyPI
npx -y apiguru-mcp     # npm

# keyless HTTP, no signup: 3 free calls/day, then x402
curl "https://agent.apiguru.app/agent/v1/v2/product-details?asin=B09DJLW458"

Everything an agent needs lives in the Agent Kit on GitHub. Machine-readable: llms.txt · OpenAPI · x402 catalogue · PyPI · npm · MCP Registry

Quick Start (Python)

1. Get Your API Key for amazon-scraper-v2

Register for a free account and get your API key:

👉 https://dash.apiguru.app/register

Free trial requests included with every account!

2. Install Dependencies

pip install requests

3. Run Examples

Each endpoint has its own simple example file. Just add your API key for amazon-scraper-v2 and run:

# Search for products
python examples/01_search_products.py

# Get product details
python examples/02_product_details.py

# Get product offers
python examples/03_product_offers.py

# Get product reviews
python examples/04_product_reviews.py

# Get best sellers
python examples/05_best_sellers.py

# Get today's deals
python examples/06_todays_deals.py

# Get seller profile
python examples/07_seller_profile.py

# Get seller products
python examples/08_seller_products.py

# Get seller reviews
python examples/09_seller_reviews.py

# Batch product details (up to 10 ASINs)
python examples/10_batch_product_details.py

API Endpoints

Product Endpoints

Seller Endpoints

Discovery Endpoints

Supported Countries

The API supports the following Amazon marketplaces:

US, CA, DE, MX, UK, FR, IT, ES, AU, BR, IN, JP, NL, AE, PL, SA, SG, SE, TR, BE

Authentication

All API requests require an API key passed via the x-api-key header:

curl -H "x-api-key: YOUR_API_KEY" "https://dash.apiguru.app/api/v1/search?query=laptop&geo=US"

Quick Example

Here's a simple example - just 20 lines of code:

import requests
import json

# Configuration
API_KEY = "YOUR_API_KEY_HERE"
BASE_URL = "https://dash.apiguru.app/api/v1"

# Search for products
response = requests.get(
    f"{BASE_URL}/search",
    headers={"x-api-key": API_KEY},
    params={
        "query": "wireless headphones",
        "geo": "US",
        "page": 1
    }
)

# Print the response
print(json.dumps(response.json(), indent=2))

That's it! Check the /examples folder for more endpoint examples.

Common Use Cases

1. Price Tracking

Monitor product prices across different sellers and countries.

import requests

response = requests.get(
    "https://dash.apiguru.app/api/v1/scrape",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={"asins": "B08C7FBW4N", "geo": "US", "condition": "new"}
)

offers = response.json()
offer_data = offers['results'][0]['data']

# Get price stats
prices = [offer['price'] for offer in offer_data]
print(f"Lowest Price: ${min(prices)}")
print(f"Highest Price: ${max(prices)}")
print(f"Total Offers: {len(offer_data)}")

2. Product Research

Find profitable products with good ratings and sales volume.

import requests

response = requests.get(
    "https://dash.apiguru.app/api/v1/v2/best-sellers",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={"geo": "US", "page": 1}
)

best_sellers = response.json()

# Filter high-rated products
for product in best_sellers['data']:
    if float(product['star_rating']) >= 4.5:
        print(f"{product['title']}")
        print(f"  Price: {product['price']}")
        print(f"  Rating: {product['star_rating']}")

3. Competitor Analysis

Monitor competitor products and pricing.

import requests

response = requests.get(
    "https://dash.apiguru.app/api/v1/seller-profile",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={"seller_ids": "A2L77EE7U53NWQ", "geo": "US"}
)

profile = response.json()
seller = profile['data']
lifetime = seller['reviews']['lifetime_reviews']

print(f"Business: {seller['business_name']}")
print(f"Total Reviews: {lifetime['reviews_count']}")
print(f"Positive: {lifetime['positive_percentage']}")

4. Review Analysis

Analyze customer sentiment and product feedback.

import requests

response = requests.get(
    "https://dash.apiguru.app/api/v1/v2/product-reviews",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={"asin": "B08C7FBW4N", "geo": "US", "page": 1}
)

data = response.json()['data']

# Analyze sentiment
positive = sum(1 for r in data['reviews'] if float(r['rating'].split()[0]) >= 4.0)
negative = sum(1 for r in data['reviews'] if float(r['rating'].split()[0]) <= 2.0)

print(f"Total Reviews: {data['total_reviews']}")
print(f"Positive: {positive}, Negative: {negative}")

5. Deal Finder

Find the best deals automatically.

import requests

response = requests.get(
    "https://dash.apiguru.app/api/v1/v2/deals",
    headers={"x-api-key": "YOUR_API_KEY"},
    params={
        "geo": "US",
        "min_product_star_rating": "4"
    }
)

deals = response.json()

# Display top d