# Xiaohongshu (RedNote) Comments Scraper - Reply Threads (`zen-studio/rednote-comments-scraper`) Actor Extract every Xiaohongshu (RedNote) comment with nested reply threads, author profile, avatar URL, IP city, like counts, attached pictures, and @-mentions. Paste note URLs or 24-character note IDs. 30+ fields per comment, export to JSON, CSV, or Excel. - **URL**: https://apify.com/zen-studio/rednote-comments-scraper.md - **Developed by:** [Zen Studio](https://apify.com/zen-studio) (community) - **Categories:** Social media, Videos, Automation - **Stats:** 3 total users, 2 monthly users, 93.8% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 comments This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## RedNote (Xiaohongshu) Comments Scraper | Nested Replies, Author Profiles, IP City (2026)
30+ fields per comment, every upstream field preserved — author profile with avatar URL, IP city, like counts, attached pictures, @-mentions, and the full nested reply tree under every comment on any Xiaohongshu (小红书) note.
![RedNote Comments Scraper](https://iili.io/BmGqX5v.png)
Zen Studio · Chinese-platform suite   •  RedNote (小红书), Douyin (抖音), Xigua (西瓜视频)
 RedNote Comments
➤ You are here 		 RedNote Search
500 notes / 30s, 24 fields 		 Douyin Search
Keyword + filters, 60+ fields 		 Douyin Transcripts
50+ languages, .srt + MP4 		 Xigua Search
Keyword + comments + MP4
#### Copy to your AI assistant ```` zen-studio/rednote-comments-scraper on Apify. Pulls every top-level comment + nested reply on any Xiaohongshu (小红书) note with author profile, avatar URL, IP city, and full target\_comment refs. Call ApifyClient("TOKEN").actor("zen-studio/rednote-comments-scraper").call(run\_input={...}), then client.dataset(run\["defaultDatasetId"]).list\_items().items. noteUrls accepts share URLs or bare 24-char hex note IDs. Full spec: GET https://api.apify.com/v2/acts/zen-studio~rednote-comments-scraper/builds/default (Bearer TOKEN) → inputSchema, actorDefinition.storages.dataset, readme. Token: https://console.apify.com/account/integrations ```` ### Key Features - **30+ fields per comment** — author profile, avatar URL, public `red_id` handle, IP city, like counts, @-mentions, attached pictures, pinned tags, the entire `target_comment` reference for every reply - **Nested reply threads** — every top-level comment carries a `replies[]` array; cap thread depth with `maxRepliesPerComment` (set to `0` for the entire tree) - **No headless browser, no proxy needed** — paste note URLs or 24-character note IDs, hit Start - **Three sort orders** — `latest`, `recommended`, `most_liked` - **Free tier** — 5 lifetime runs, ~20 comments from the first note, no credit card ### How to Scrape Xiaohongshu Comments #### Basic — single note, default settings ```json { "noteUrls": ["https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8"] } ```` #### Multiple notes, capped budget ```json { "noteUrls": [ "https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8", "69dc63550000000015004853" ], "maxCommentsPerNote": 200, "maxRepliesPerComment": 10 } ``` #### Top-voted threads only, no replies ```json { "noteUrls": ["69db721a00000000220290a8"], "sortBy": "most_liked", "includeReplies": false, "maxCommentsPerNote": 50 } ``` #### Full thread tree for one viral comment ```json { "noteUrls": ["69db721a00000000220290a8"], "maxCommentsPerNote": 1, "maxRepliesPerComment": 0 } ``` ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `noteUrls` | array | *required* | One or more Xiaohongshu note links or bare 24-character note IDs. Each note runs independently. | | `sortBy` | enum | `latest` | `latest`, `recommended`, or `most_liked` | | `includeReplies` | boolean | `true` | When `true`, every comment carries a nested `replies[]` array | | `maxRepliesPerComment` | integer | `5` | Replies to fetch under each top-level comment. `0` = unlimited | | `maxCommentsPerNote` | integer | `0` | Top-level comments per note. `0` = all | ### What Data Can You Extract from Xiaohongshu Comments? Every dataset row is one top-level comment with its full reply thread nested inside. **Comment fields:** - `id`, `note_id`, `url_to_note`, `content`, `time` - `like_count`, `sub_comment_count`, `liked`, `ip_location` - `pictures` (when the comment has attached images) - `show_tags`, `show_tags_v2` (includes `Pinned`, `Author liked` labels) - `at_users`, `hash_tags`, `media_source_type` - `sort_by`, `comment_index_in_note` **Author profile (`user`):** - `userid`, `red_id` (public XHS handle), `nickname` - `images` (avatar URL), `ai_agent`, `level` **Each nested reply (`replies[]`):** - All the comment fields above (where applicable) - `target_comment` with the parent's `id`, `status`, and full `user` profile #### Output Example ```json { "id": "69dc63550000000015004853", "note_id": "69db721a00000000220290a8", "url_to_note": "https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8", "content": "千万不要点进作者的主页，不然就出不来了[捂脸R][捂脸R]", "time": 1776051029, "ip_location": "Shanghai", "like_count": 119, "sub_comment_count": 11, "liked": false, "collected": false, "user": { "userid": "ae72f2a6105526a05fb17d369ee6e", "red_id": "27209397831", "nickname": "晚风轻吟", "images": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31uu4q7413q005qca0u389c1cvfo51i0?imageView2/2/w/120/format/jpg", "ai_agent": false, "level": { "image": "" }, "current_user": "false", "additional_tags": {} }, "at_users": [], "show_tags": [], "show_tags_v2": [ { "text": "Pinned", "type": "user_top", "pos": "cmt_bottom", "style_id": "red" } ], "pictures": null, "hash_tags": null, "media_source_type": null, "sub_comment_cursor": "{\"cursor\":\"69dc6a7d000000001500ab19\",\"index\":1}", "replies": [ { "id": "69dc6a7d000000001500ab19", "content": "不信你的话，点进去第一反应就是咽了几口口水[暗中观察R]", "time": 1776052862, "ip_location": "Guangdong", "like_count": 93, "liked": false, "user": { "userid": "a651518b161bd8d20adb86abd4798", "red_id": "4646143817", "nickname": "八方来财", "images": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31q83819h7u005pdi1p9kpa9hcpnh30g?imageView2/2/w/120/format/jpg", "ai_agent": false }, "target_comment": { "id": "69dc63550000000015004853", "status": 4, "user": { "userid": "ae72f2a6105526a05fb17d369ee6e", "red_id": "27209397831", "nickname": "晚风轻吟", "images": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31uu4q7413q005qca0u389c1cvfo51i0?imageView2/2/w/120/format/jpg" } }, "at_users": [], "show_tags": [], "show_tags_v2": [ { "text": "Author liked", "type": "author_liked" } ] }, { "id": "69dc736a000000001500a5a1", "content": "果然 不关注都出不来[笑哭R]", "time": 1776055146, "ip_location": "Beijing", "like_count": 2, "user": { "userid": "6539e3ce000000000d006d07", "red_id": "4583774467", "nickname": "熙熙大王", "images": "https://sns-avatar-qc.xhscdn.com/avatar/1040g2jo31iojfqsd1a605p9psf738r870uj84a8?imageView2/2/w/120/format/jpg" }, "target_comment": { "id": "69dc63550000000015004853", "user": { "userid": "698a0786000000002100b02c", "nickname": "晚风轻吟" } }, "show_tags": ["author_liked"] } // ... 3 more replies ], "sort_by": "latest", "comment_index_in_note": 0, "status": 4, "score": 10000000, "hidden": false, "downvoted": false, "share_strategy": 0, "comment_type": 0, "translation_strategy": 9, "show_type": "common", "relatable_to_note": false, "biz_label": { "product_review": false, "group_invite": "false", "rich_text": "unknown" }, "track_id": "interaction-service.local", "friend_liked_msg": "", "sub_comments": [ // raw upstream `sub_comments` inline (mirrors the first entry of `replies`) ] } ``` ### Advanced Usage #### Cap cost on a viral note ```json { "noteUrls": ["69db721a00000000220290a8"], "maxCommentsPerNote": 100, "maxRepliesPerComment": 3 } ``` #### Bulk-collect comments from a known set of notes ```json { "noteUrls": [ "69db721a00000000220290a8", "69dc63550000000015004853", "69dcf76e000000003501618e" ], "sortBy": "most_liked", "maxCommentsPerNote": 50 } ``` #### IP-city sentiment study — top comments only ```json { "noteUrls": ["69db721a00000000220290a8"], "sortBy": "most_liked", "includeReplies": false, "maxCommentsPerNote": 500 } ``` ### Pricing — Pay Per Event (PPE) **$5.99 per 1,000 comments.** Each comment counts as one billable result — both top-level comments and nested replies. | Event | Per call | Per 1,000 | |-------|----------|-----------| | Comment result (top-level or nested reply) | $0.00599 | $5.99 | Free tier: 5 lifetime runs, ~20 comments from the first note, replies off. ### FAQ **Which note URL formats are accepted?** Full share URLs (`/discovery/item/` or `/explore/`, with or without `xsec_token` query params) and bare 24-character hex IDs. **Why does my dataset have fewer rows than I expected?** Each row is one top-level comment, with the full reply tree embedded inside its `replies[]` array. If you ran with `maxCommentsPerNote: 50`, you get up to 50 rows — but the total billed comments include every nested reply too. **What's IP location?** Xiaohongshu attaches a coarse geographic label to each comment (province or city, e.g. `Beijing`, `Shanghai`, `Guangdong`). Roughly 70% of top-level comments and 50% of replies carry it. **Are author avatars included?** Yes — `user.images` on every comment and reply is a direct CDN URL to the author's avatar. **Can I get the full reply tree under one comment?** Yes. Set `maxRepliesPerComment: 0` and target the comment by pinning its note (`maxCommentsPerNote: 1`) — the scraper paginates all replies until the upstream cursor exhausts. **What sort orders are supported?** `latest` (newest first, the Xiaohongshu app default), `recommended` (curated relevance), `most_liked` (by like count). **Can I detect pinned comments?** Yes — `show_tags_v2` carries a `{ "type": "user_top", "text": "Pinned" }` entry on the pinned comment. **Does the actor follow `@`-mentions?** The `at_users` array on each comment lists the mentioned users with `user_id` and `nickname`. The scraper does not recursively fetch their profiles. **What happens if a note has comments disabled or is removed?** You'll get zero comments for that note ID and the run continues with the next note. **How fresh is the data?** Live from Xiaohongshu at run time — no cache. ### Support - **Bugs**: Issues tab - **Features**: Issues tab ### Legal Compliance Extracts publicly available data. Users must comply with Xiaohongshu's terms and data protection regulations (GDPR, CCPA). *** *Pull every top-level comment and nested reply on any Xiaohongshu (小红书) note with author profile, avatar URL, IP city, like counts, and the full target\_comment reference for each reply.* # Actor input Schema ## `noteUrls` (type: `array`): Add one or more Xiaohongshu note links. Bare 24-character note IDs work too.

• Full URL: https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8?xsec\_token=...
• Bare ID: 69db721a00000000220290a8

Each note runs independently with its own Max comments per note budget. ## `sortBy` (type: `string`): How comments are ranked.

• Latest — newest first (default; matches the Xiaohongshu app's own default)
• Recommended — Xiaohongshu's curated relevance ranker
• Most liked — by like count; surfaces the top-voted threads ## `includeReplies` (type: `boolean`): When ON (default), every top-level comment row carries a nested replies\[] array.

Turn OFF to scrape only top-level comments and keep cost predictable.

Each reply counts as one billable result — use Max replies per comment to cap thread depth. ## `maxCommentsPerNote` (type: `integer`): Top-level comments to collect per note. Set to 0 to fetch all.

Use this on viral notes (a single trending note can have 1,000+ comments). ## `maxRepliesPerComment` (type: `integer`): How many replies to fetch under each top-level comment. Set to 0 for all replies (no cap).

Each reply counts as one billable result, so this is the most effective lever for viral notes with deep reply threads. ## Actor input object example ```json { "noteUrls": [ "https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8" ], "sortBy": "latest", "includeReplies": true, "maxCommentsPerNote": 0, "maxRepliesPerComment": 5 } ``` # Actor output Schema ## `results` (type: `string`): Dataset of comments — one row per top-level comment with nested replies. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "noteUrls": [ "https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8" ] }; // Run the Actor and wait for it to finish const run = await client.actor("zen-studio/rednote-comments-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "noteUrls": ["https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8"] } # Run the Actor and wait for it to finish run = client.actor("zen-studio/rednote-comments-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "noteUrls": [ "https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8" ] }' | apify call zen-studio/rednote-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=zen-studio/rednote-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Xiaohongshu (RedNote) Comments Scraper - Reply Threads", "description": "Extract every Xiaohongshu (RedNote) comment with nested reply threads, author profile, avatar URL, IP city, like counts, attached pictures, and @-mentions. Paste note URLs or 24-character note IDs. 30+ fields per comment, export to JSON, CSV, or Excel.", "version": "0.0", "x-build-id": "Iy5xdhCM4aQYLFrSD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/zen-studio~rednote-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-zen-studio-rednote-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/zen-studio~rednote-comments-scraper/runs": { "post": { "operationId": "runs-sync-zen-studio-rednote-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/zen-studio~rednote-comments-scraper/run-sync": { "post": { "operationId": "run-sync-zen-studio-rednote-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "noteUrls" ], "properties": { "noteUrls": { "title": "🔗 Note URLs or IDs", "minItems": 1, "type": "array", "description": "Add one or more Xiaohongshu note links. Bare 24-character note IDs work too.

• Full URL: https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8?xsec_token=...
• Bare ID: 69db721a00000000220290a8

Each note runs independently with its own Max comments per note budget.", "items": { "type": "string" } }, "sortBy": { "title": "Sort comments by", "enum": [ "latest", "recommended", "most_liked" ], "type": "string", "description": "How comments are ranked.

• Latest — newest first (default; matches the Xiaohongshu app's own default)
• Recommended — Xiaohongshu's curated relevance ranker
• Most liked — by like count; surfaces the top-voted threads", "default": "latest" }, "includeReplies": { "title": "Include replies under each comment", "type": "boolean", "description": "When ON (default), every top-level comment row carries a nested replies[] array.

Turn OFF to scrape only top-level comments and keep cost predictable.

Each reply counts as one billable result — use Max replies per comment to cap thread depth.", "default": true }, "maxCommentsPerNote": { "title": "Max comments per note", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Top-level comments to collect per note. Set to 0 to fetch all.

Use this on viral notes (a single trending note can have 1,000+ comments).", "default": 0 }, "maxRepliesPerComment": { "title": "Max replies per comment", "minimum": 0, "maximum": 1000, "type": "integer", "description": "How many replies to fetch under each top-level comment. Set to 0 for all replies (no cap).

Each reply counts as one billable result, so this is the most effective lever for viral notes with deep reply threads.", "default": 5 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```