How to use 1688 Products Scraper

Step by step: in the Apify Store, over the API, from JavaScript or Python, in n8n, and from AI agents through MCP or LangChain.

$1.80 per 1,000 product (search result)s on the Free plan, down to $1.35 on higher plans (live Apify price on 2026-11-01).

1. In the Apify Store (no code)

1. Open arcadium/1688-products and sign in to Apify (a free account works).
2. Fill in the input form. The fields below are the ones the example uses.
3. Set a maximum cost per run in the run options if you want a hard cap.
4. Start the run. Rows appear in the Output tab as they arrive.
5. Export the dataset as JSON, CSV or Excel, or connect an integration.

Example input:

{
  "keywords": [
    "保温杯"
  ],
  "maxItemsPerKeyword": 50,
  "sort": "relevance",
  "includeDetails": false
}

2. Over the Apify API

The synchronous endpoint runs the actor and returns its rows in one call (for runs up to about five minutes; use the asynchronous run endpoint for longer ones).

curl -X POST "https://api.apify.com/v2/acts/arcadium~1688-products/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords":["保温杯"],"maxItemsPerKeyword":50,"sort":"relevance","includeDetails":false}'

3. From JavaScript

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/1688-products').call({
  "keywords": [
    "保温杯"
  ],
  "maxItemsPerKeyword": 50,
  "sort": "relevance",
  "includeDetails": false
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

4. From Python

# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/1688-products").call(run_input={
    "keywords": ["保温杯"],
    "maxItemsPerKeyword": 50,
    "sort": "relevance",
    "includeDetails": False,
})
items = client.dataset(run.default_dataset_id).list_items().items  # apify-client 3.x returns a Run object
print(items)

5. In n8n

Paste this node into a workflow (it is a plain HTTP Request node). Create a Header Auth credential with name Authorization and value Bearer <APIFY_TOKEN>; each returned row becomes one item for the next node.

{
  "nodes": [
    {
      "name": "Run arcadium/1688-products",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~1688-products/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"keywords\":[\"保温杯\"],\"maxItemsPerKeyword\":50,\"sort\":\"relevance\",\"includeDetails\":false}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}

6. From an AI assistant (MCP)

Add Apify’s MCP server to Claude Desktop, Cursor, VS Code or any MCP client, limited to this actor:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/1688-products",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}

More on the MCP page.

7. From LangChain

# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/1688-products")
rows = tool.invoke({"run_input": {
    "keywords": ["保温杯"],
    "maxItemsPerKeyword": 50,
    "sort": "relevance",
    "includeDetails": False,
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])

Sample output

One row, from the example in the actor’s README. Long text is shortened and lists are cut to two items.

{
  "rowType": "product",
  "platform": "1688",
  "offerId": "866095761513",
  "url": "https://detail.1688.com/offer/866095761513.html",
  "title": "数据线保护套硅胶防折断充电线保护套咬线器防断裂神器",
  "keyword": "数据线",
  "rank": 2,
  "isAd": false,
  "currency": "CNY",
  "priceMin": 2.5,
  "priceMax": 2.6,
  "priceTiers": [
    {
      "minQty": 3,
      "maxQty": 4999,
      "price": 2.6
    },
    {
      "minQty": 5000,
      "maxQty": 99999,
      "price": 2.55
    }
  ],
  "moq": 3,
  "unit": "件",
  "soldCount": 100000,
  "soldText": "已售10万+件",
  "soldScope": "offer",
  "repurchaseRate": 17,
  "origin": {
    "province": "广东",
    "city": "东莞市"
  },
  "supplier": {
    "companyName": "东莞市元拓橡塑制品有限公司",
    "memberId": "b2b-22072902285003c713",
    "isFactory": true,
    "yearsOnPlatform": 7,
    "serviceScores": {
      "composite": 4,
      "consultation": 4,
      "logistics": 3.57,
      "dispute": 5,
      "returns": 3.67,
      "goods": 3.33
    },
    "repurchaseRate3m": 77,
    "shopUrl": "https://apetop.1688.com"
  },
  "hasDetails": false
}

Tutorials

• Find 1688 factory prices for a product idea

Schedule it

In Apify Console, create a Task from your input and add a Schedule (for example daily). Each run writes a new dataset; integrations can push the rows to Google Sheets, Slack, a webhook or your database.