Alibaba Product Search Scraper extracts Alibaba.com product search results for e-commerce sourcing, supplier discovery, price/MOQ research, and product lead exports.
Value proposition
Get structured Alibaba product search data without manually copying result cards.
What does this actor do?
Alibaba Product Search Scraper exports product results from Alibaba.com for sourcing, supplier discovery, and product research. Each dataset row contains product titles, Alibaba product URLs, price text, MOQ/minimum order text, supplier signals, images, and the source query.
Who is it for and use cases
- Sourcing teams: build a shortlist of products and suppliers for buyer outreach.
- E-commerce researchers: compare visible price ranges, MOQ text, and product positioning.
- Market analysts: monitor Alibaba search results for recurring product categories.
- Lead generation teams: collect product URLs and supplier names for follow-up workflows.
Input example
{
"queries": ["solar panel", "yoga mat"],
"maxItemsPerQuery": 10,
"maxRetriesPerQuery": 1
}
Verified public examples
Ready-to-run Apify Store examples verified in post-publish QA:
Input settings
| Field | Type | Description |
|---|---|---|
queries |
string[] | Alibaba search phrases to run. |
maxItemsPerQuery |
integer | Maximum product rows to save per query. |
navigationTimeoutMs |
integer | Bounded timeout for fallback browser navigation. |
maxRetriesPerQuery |
integer | Retries for transient empty or blocked browser pages. |
proxyConfiguration |
object | Apify Proxy settings. Residential proxy is recommended when the browser fallback is needed. |
Output example
{
"query": "solar panel",
"rank": 1,
"title": "Bluesun Solar Panel 700w 710w 720w Best Panel Bifacial Solar Panel",
"url": "https://www.alibaba.com/product-detail/example_1600000000000.html",
"priceText": "$61.2 - $63.36",
"moqText": null,
"supplierName": "Bluesun Solar Co., Ltd.",
"supplierLocation": "China",
"verifiedSupplier": true,
"tradeAssurance": false,
"imageUrl": "https://s.alicdn.com/example.jpg",
"sourceUrl": "https://open-s.alibaba.com/openservice/...",
"scrapedAt": "2026-07-24T21:55:08.000Z"
}
API usage
Node.js
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/alibaba-runtime-spike').call({
queries: ['solar panel'],
maxItemsPerQuery: 10,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
Python
from apify_client import ApifyClient
import os
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/alibaba-runtime-spike').call(run_input={
'queries': ['solar panel'],
'maxItemsPerQuery': 10,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)
cURL
curl -X POST "https://api.apify.com/v2/acts/fetch_cat~alibaba-runtime-spike/runs?token=$APIFY_TOKEN" \
-H 'Content-Type: application/json' \
-d '{"queries":["solar panel"],"maxItemsPerQuery":10}'
MCP and AI agents
Use this actor from Apify MCP-compatible tools to give AI agents Alibaba product search data. Start with narrow queries and low maxItemsPerQuery values, then increase limits after checking result quality.
Claude CLI setup example:
claude mcp add apify -- npx -y @apify/actors-mcp-server --actors fetch_cat/alibaba-runtime-spike
MCP JSON config example:
{
"mcpServers": {
"apify": {
"command": "npx",
"args": ["-y", "@apify/actors-mcp-server", "--actors", "fetch_cat/alibaba-runtime-spike"],
"env": { "APIFY_TOKEN": "YOUR_APIFY_TOKEN" }
}
}
}
Example prompts:
- "Find 10 Alibaba solar panel product results and summarize common supplier signals."
- "Export Alibaba yoga mat product URLs with price and MOQ text."
- "Compare visible Alibaba search results for phone cases and screen protectors."
Support
When opening an issue, include your input JSON, expected output, actual output, and a reproducible public URL for the run, such as an Apify Console run URL or run ID.
