# How to export Xiaohongshu comments for a keyword

> Search Xiaohongshu notes by keyword, keep the ones people discussed most, then page through their comments into one CSV: the two endpoints, parameters, code and cost.

Canonical page: https://okdata.online/guides/xiaohongshu-note-comments/

Two endpoints: Xiaohongshu note search, then Xiaohongshu note comments for each note you keep. The worked example below is 7 calls and costs $0.14; a failed call is not charged.

Updated 2026-11-12

The job: you are about to launch a product, or you sell against one, and you want to know what Xiaohongshu users actually say about the category. Notes show what creators want you to think; the comments under them show what readers ask, doubt and compare. So you search a keyword, keep the notes that drew the most discussion, and read their comment sections a page at a time. You end with one CSV: note title, comment text, commenter, likes, reply count, time and the IP region Xiaohongshu shows next to each comment.

No Xiaohongshu account, cookie or xsec_token is involved. Each call is an HTTPS request with your key.

## Step by step

### Step 1: find the notes worth reading

Call [Xiaohongshu note search](https://okdata.online/apis/xiaohongshu/notes/search/) with `query`, written the way people type it into the app: `防晒霜`, `防晒霜 油皮`, `敏感肌 防晒`. Two parameters matter here:

- `sort`: `general` (the default, Xiaohongshu's own mix), `latest` or `popular`. For comment mining, `popular` surfaces the notes with the most engagement, which are usually the ones with real discussion.
- `type`: `all` (the default), `video` or `image`. Leave it at `all` unless you only care about one format.

One call returns about 20 notes for $0.02. Each has `id` (24 hex characters), `title`, the start of the text, `author`, `published_at` and `metrics` with likes, favorites (saves) and comments. Sort on `metrics.comments` to pick the notes to open.

```bash
curl -G "https://api.okdata.online/v1/xiaohongshu/notes/search" \
  -H "Authorization: Bearer $OKDATA_API_KEY" \
  --data-urlencode 'query=防晒霜' \
  --data-urlencode 'sort=popular' \
  --data-urlencode 'fields=id,title,metrics.comments,metrics.likes,published_at'
```

`fields` keeps the response short without changing the price.

### Step 2: page through the comments

Pass a note's `id` to [Xiaohongshu note comments](https://okdata.online/apis/xiaohongshu/notes/comments/list/). One call returns about 10 top-level comments for $0.02. Each has `text`, `author` (name and ID), `likes`, `replies` (how many replies sit under it), `published_at` and `ip_location`. `parent_id` is null because these are top-level comments. For the next page, send `page.next_cursor` back as `cursor`, unchanged; stop when `page.has_more` is `false`.

```bash
curl -G "https://api.okdata.online/v1/xiaohongshu/notes/comments/list" \
  -H "Authorization: Bearer $OKDATA_API_KEY" \
  --data-urlencode 'id=672a4f1d000000001b03c58e'
```

Comment pages are small on Xiaohongshu, so budget by pages, not by notes: 1,000 comments take about 100 calls.

### Step 3: put it together in Python

The script searches once, keeps the 3 notes with the most comments, reads up to `MAX_PAGES` pages under each and writes one CSV.

```python
import csv
import os
import requests

API = "https://api.okdata.online"
HEADERS = {"Authorization": f"Bearer {os.environ['OKDATA_API_KEY']}"}
NOTES = 3      # notes to open
MAX_PAGES = 2  # comment pages per note; each page is one call


def get(path, **params):
    body = requests.get(API + path, headers=HEADERS, params=params, timeout=60).json()
    if body["code"] != "ok":
        raise RuntimeError(f"{body['code']}: {body['message']} (charged: {body['charged']})")
    return body


notes = get("/v1/xiaohongshu/notes/search", query="防晒霜", sort="popular")["data"]["items"]
notes = sorted(notes, key=lambda n: n["metrics"]["comments"] or 0, reverse=True)[:NOTES]

with open("xhs_comments.csv", "w", newline="", encoding="utf-8-sig") as f:
    out = csv.writer(f)
    out.writerow(["note_id", "note_title", "comment", "user", "likes", "replies", "ip_location", "published_at"])
    for n in notes:
        cursor = None
        for _ in range(MAX_PAGES):
            params = {"id": n["id"], **({"cursor": cursor} if cursor else {})}
            body = get("/v1/xiaohongshu/notes/comments/list", **params)
            for c in body["data"]["items"]:
                out.writerow([n["id"], n["title"], c["text"], c["author"]["name"], c["likes"],
                              c["replies"], c["ip_location"], c["published_at"]])
            if not body["page"]["has_more"]:
                break
            cursor = body["page"]["next_cursor"]
```

Raise `NOTES` and `MAX_PAGES` to go wider and deeper. Ten notes at five pages each is 50 comment calls, $1.00 on top of the search. Per 1,000 comments the bill comes to about $2.00.

## Good to know

- **Counts will not match the note.** The comment count on a note includes replies. This endpoint lists top-level comments and gives each one's reply count in `replies`, not the reply text, so you collect fewer rows than `metrics.comments`.
- **Order.** Comments come in Xiaohongshu's default order; there is no sort parameter, and no newest-first option.
- **IP region.** `ip_location` is the province or country label Xiaohongshu prints next to a comment. It is null when Xiaohongshu shows none.
- **No token juggling.** You pass the note ID only. Why that matters on Xiaohongshu is in [the xsec_token answer](https://okdata.online/answers/xiaohongshu-xsec-token/).
- **Deleted notes are free.** A note that is gone or private returns `not_found` and costs nothing; skip it.
- **Retries without paying twice.** Send an `Idempotency-Key` header with each call. The same request with the same key within 24 hours returns the stored answer with `meta.replayed: true` and no new charge.

To export every comment under one note you already have, see [how to export a Xiaohongshu note's comments](https://okdata.online/answers/xiaohongshu-export-note-comments/). For turning comments into a list of complaints and questions, see [finding pain points in Douyin and Xiaohongshu comments with an LLM](https://okdata.online/answers/llm-comment-pain-points-douyin-xiaohongshu/).

## What the example costs

One page of the most popular notes for 防晒霜 (sunscreen), then two pages of comments under each of the 3 notes with the most comments

| Endpoint | Calls | Price | Subtotal |
|---|---|---|---|
| [Xiaohongshu note search](https://okdata.online/apis/xiaohongshu/notes/search/) | 1 | $0.02 | $0.02 |
| [Xiaohongshu note comments](https://okdata.online/apis/xiaohongshu/notes/comments/list/) | 6 | $0.02 | $0.12 |
| Total | 7 |  | $0.14 |

Prices in force when this page was built. A failed call costs nothing.

## In your AI (MCP)

Connect the MCP server once, then say what you want. The agent finds these endpoints, reads their prices and calls them on your balance.

Say: Search Xiaohongshu for 防晒霜 (sunscreen), most popular first, take the 3 notes with the most comments, read two pages of comments under each and give me one table: note title, comment, likes, replies, IP location, time.

```json
{
  "endpoint": "xiaohongshu.notes.search",
  "params": {
    "query": "防晒霜 推荐"
  },
  "idempotency_key": "<a new UUID>"
}
```

MCP: `https://api.okdata.online/mcp`

## Endpoints in this guide

- [Xiaohongshu note search](https://okdata.online/apis/xiaohongshu/notes/search/) `xiaohongshu.notes.search`: $0.02 per call · about 20 notes per page
- [Xiaohongshu note comments](https://okdata.online/apis/xiaohongshu/notes/comments/list/) `xiaohongshu.notes.comments.list`: $0.02 per call · about 10 comments per page

## More about Xiaohongshu (RedNote)

- [Xiaohongshu (RedNote) API](https://okdata.online/apis/xiaohongshu/)
- [Xiaohongshu API in Python: notes, profiles and comments (2026)](https://okdata.online/guides/xiaohongshu-api-python/)
- [How to shortlist Xiaohongshu PGY creators by rate and reads](https://okdata.online/guides/xiaohongshu-pgy-creator-rates/)
- [How to search Xiaohongshu notes and export them to CSV](https://okdata.online/guides/xiaohongshu-search-export-notes/)
- [How do I add Xiaohongshu data to Cursor or Cline through MCP?](https://okdata.online/answers/cursor-cline-xiaohongshu-mcp/)
- [How do I use an LLM to find customer pain points in Douyin and Xiaohongshu comments?](https://okdata.online/answers/llm-comment-pain-points-douyin-xiaohongshu/)
- [MediaCrawler keeps breaking for me. Is a paid API worth it instead?](https://okdata.online/answers/mediacrawler-alternative-paid-api/)
- [Is there an MCP or API version of MediaCrawler for AI agents?](https://okdata.online/answers/mediacrawler-mcp-for-ai-agents/)
- [Is it cheaper to run my own social media scraper or pay for an API?](https://okdata.online/answers/self-hosted-scraper-vs-api-cost/)
- [How do I find complaints about a brand on Xiaohongshu?](https://okdata.online/answers/xiaohongshu-brand-complaints/)
- [Scraping it yourself vs a per-call data API: cost, upkeep and risk](https://okdata.online/compare/scraping-vs-data-api/)
- [How to choose a social media data API (2026)](https://okdata.online/compare/social-media-data-apis/)
- [MCP servers for social media data: self-hosted vs hosted](https://okdata.online/compare/social-media-data-mcp-servers/)
- [Xiaohongshu data APIs: official, third-party or open-source (2026)](https://okdata.online/compare/xiaohongshu-data-apis/)