RedNote Xiaohongshu Search Scraper

What is RedNote Xiaohongshu Note Search Scraper?

Search RedNote (Xiaohongshu / 小红书) note cards by one keyword through an authorized logged-in session and get one record per public note card. This Actor accepts a search keyword plus your session cookie, and it returns structured note cards with the note ID, source URL, search query, result position, title, creator name, creator URL when rendered, cover image when present, likes text, normalized likes count when parseable, and scrape time. The outcome is a dataset of public search results that can be used for market research, trend discovery, and content monitoring.

Best fit and connected workflows

This Actor fits workflows where the goal is to collect public Xiaohongshu search cards for a single keyword and review them as structured rows. It works well when you want to:

• track how a keyword surfaces public note cards over time,
• compare titles, creators, and engagement text from search results,
• feed note-card rows into analysis, triage, or reporting tools,
• use Apify API, Apify Console, or Apify MCP to run the search and read the dataset.

focused workflow

RedNote Xiaohongshu Note Search Scraper is designed as a focused workflow.

Practical scenario

A market researcher wants to review public RedNote search results for the keyword "护肤". They start with a logged-in Xiaohongshu browser session cookie and a target result cap. The Actor returns note-card rows with title, authorName, likesText, likesCount, and sourceUrl. The researcher compares which creators and note titles appear near the top of the search results, then opens the source URLs that look most relevant for manual review.

Input

Field	Type	Required	Description
searchQuery	string	Yes	One RedNote/Xiaohongshu search keyword, such as 护肤 or skincare tips. Up to 100 characters.
maxResults	integer	No	Maximum number of unique public note cards to save. Minimum 1, maximum 100, default 20.
sessionCookie	string	Yes	Cookie header from your own authorized logged-in Xiaohongshu browser session. Treated as a secret.

Focused JSON input example

{
  "searchQuery": "护肤",
  "maxResults": 20,
  "sessionCookie": "web_session=example"
}

Output

Field	Type	Description
id	string	Public Xiaohongshu note identifier parsed from the note URL.
sourceUrl	string	Canonical public note URL returned by search.
searchQuery	string	Keyword used to collect the note card.
resultPosition	integer	One-based position of the note card in the rendered search page.
title	string or null	Public title text when rendered.
authorName	string or null	Creator display name shown on the search card.
authorUrl	string or null	Public creator-profile URL when rendered.
coverImageUrl	string or null	Public cover-image URL when present.
likesText	string or null	Engagement text displayed in the search card.
likesCount	integer or null	Normalized like count parsed from the displayed text when possible.
scrapedAt	string	ISO 8601 time when the card was collected.

Illustrative output record

{
  "id": "1234567890",
  "sourceUrl": "https://www.xiaohongshu.com/explore/1234567890",
  "searchQuery": "护肤",
  "resultPosition": 1,
  "title": "护肤分享",
  "authorName": "Creator Name",
  "authorUrl": "https://www.xiaohongshu.com/user/profile/creator-id",
  "coverImageUrl": "https://example.com/cover.jpg",
  "likesText": "1.2万",
  "likesCount": 12000,
  "scrapedAt": "2026-01-01T00:00:00.000Z"
}

How it works

The Actor runs a browser-based search flow for Xiaohongshu note cards using your authorized session cookie. It collects public search-result cards that are rendered for the submitted keyword, then saves each validated card as one dataset record. The dataset view is shaped for table-style review with position, title, creator, likes, note URL, query, and scrape time. The run also writes compact run outputs to the default key-value store.

Pricing

RedNote Xiaohongshu Note Search Scraper uses Pay per event pricing plus Apify platform usage. The charged events are:

• Actor start: charged once per run.
• Xiaohongshu search result: charged once for each validated public note card saved to the dataset.

For current pricing details, open the live Pricing tab on the Actor page. As an example, a run that saves twenty search-result cards will include twenty search-result events plus one actor-start event, and platform usage is billed separately.

Use with AI agents (MCP)

This Actor is usable through Apify MCP as an Apify Actor tool for running a Xiaohongshu keyword search and reading the resulting dataset rows. The exact Actor identity is khadinakbar/xiaohongshu-search-scraper.

Search Xiaohongshu note cards for the keyword "护肤" using my authorized session cookie. Return the dataset rows with title, creator, likes, source URL, result position, and scrape time. Use a maximum of 20 results and summarize the run outcome from the output records.

When interpreted by an AI agent, the dataset rows represent public search-card records only. likesText preserves the engagement text as displayed, while likesCount is the normalized numeric parse when available. scrapedAt provides collection time, and resultPosition reflects the rendered search order. The results output points to the dataset items endpoint, so agents can page or read back the records after the run. Event cost grows with the number of validated cards saved, so agent prompts should set an appropriate maxResults value.

JavaScript Apify API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const input = {
  searchQuery: '护肤',
  maxResults: 20,
  sessionCookie: process.env.XHS_SESSION_COOKIE,
};

const run = await client.actor('khadinakbar/xiaohongshu-search-scraper').call(input);

const { items } = await client.dataset(run.defaultDatasetId).listItems();

console.log('Dataset items:', items);

Best results and outcome guidance

Use a keyword that matches the public notes you want to review, and keep maxResults aligned with the number of cards you actually need. Since the Actor returns search-result cards rather than full note pages, profile catalogs, or comments, the most direct workflow is to search a topic, inspect the returned note titles and creators, and open selected sourceUrl values for manual follow-up.

Continue the workflow

• Then use Bluesky Posts Scraper — Search, Feeds & Threads to extend RedNote Xiaohongshu Note Search Scraper with a neighboring social-media research source when the brief calls for Bluesky data.
• Then use X Twitter Trends Scraper - Country Trends API to extend RedNote Xiaohongshu Note Search Scraper with a neighboring social-media research source when the brief calls for X Twitter data.

Design note

I found that the live dataset contract requires id, sourceUrl, searchQuery, and scrapedAt on every record, which makes each saved card traceable back to its query and collection time.

FAQ

Is this Actor for one keyword at a time?

Yes. The input schema is centered on a single searchQuery value, which keeps each run tied to one search topic.

What kind of results does it return?

It returns public Xiaohongshu search-result note cards with fields such as title, creator, likes, URL, and scrape time.

Does it return note details or comments?

This Actor is built for search-result cards from Xiaohongshu keyword search. It returns the rendered cards in the search results dataset.

How do I use it in a workflow with Apify API or MCP?

Run the Actor with your keyword and authorized session cookie, then read the dataset items from the default dataset URL or through the Apify API. The same Actor can also be called through Apify MCP.

How is pricing applied?

Pricing follows Pay per event plus Apify platform usage. Search-result events are charged per validated public note card saved, and the live Pricing tab shows the current rates.

Responsible use

Use this Actor only with an authorized session and in accordance with applicable law and platform rules. It is designed for public search-card collection from Xiaohongshu and for lawful research, monitoring, and analysis workflows.