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Skills/zhjiang22/openclaw-xhs/xiaohongshu
xiaohongshu logo

xiaohongshu

zhjiang22/openclaw-xhs
10K installs106 stars
Run it on Hostinger →up to 70% off + an extra 10% with code ZACAARON10Free API →

Installation

npx skills add https://github.com/zhjiang22/openclaw-xhs --skill xiaohongshu

Summary

|

SKILL.md

小红书 MCP Skill

基于 xiaohongshu-mcp 封装的 shell 脚本工具集。

前置条件

cd scripts/
./install-check.sh    # 检查依赖(xiaohongshu-mcp、jq、python3)
./start-mcp.sh        # 启动 MCP 服务(默认端口 18060)
./status.sh           # 确认已登录

未登录时需扫码:mcp-call.sh get_login_qrcode 获取二维码,用小红书 App 扫码。

服务端口可通过 MCP_URL 环境变量覆盖(默认 http://localhost:18060/mcp)。

核心数据流

重要: 大多数操作需要 feed_id + xsec_token 配对。这两个值从搜索/推荐/用户主页结果中获取,不可自行构造。

search_feeds / list_feeds / user_profile
        │
        ▼
  返回 feeds 数组,每个 feed 包含:
  ├── id          → 用作 feed_id
  ├── xsecToken   → 用作 xsec_token
  └── noteCard    → 标题、作者、封面、互动数据
        │
        ▼
  get_feed_detail(feed_id, xsec_token)
        │
        ▼
  返回完整笔记: 正文、图片列表、评论列表
  评论中包含 comment_id、user_id(用于回复评论)

脚本参考

脚本用途参数
search.sh <关键词>搜索笔记关键词
recommend.sh首页推荐无
post-detail.sh <feed_id> <xsec_token>帖子详情+评论从搜索结果获取
comment.sh <feed_id> <xsec_token> <内容>发表评论从搜索结果获取
user-profile.sh <user_id> <xsec_token>用户主页+笔记从搜索结果获取
track-topic.sh <话题> [选项]热点分析报告--limit N --output file --feishu
export-long-image.sh帖子导出长图--posts-file json -o output.jpg
mcp-call.sh <tool> [json_args]通用 MCP 调用见下方工具表
start-mcp.sh启动服务--headless=false --port=N
stop-mcp.sh停止服务无
status.sh检查登录无
install-check.sh检查依赖无

MCP 工具详细参数

search_feeds — 搜索笔记

{"keyword": "咖啡", "filters": {"sort_by": "最新", "note_type": "图文", "publish_time": "一周内"}}

filters 可选字段:

  • sort_by: 综合 | 最新 | 最多点赞 | 最多评论 | 最多收藏
  • note_type: 不限 | 视频 | 图文
  • publish_time: 不限 | 一天内 | 一周内 | 半年内
  • search_scope: 不限 | 已看过 | 未看过 | 已关注
  • location: 不限 | 同城 | 附近

get_feed_detail — 帖子详情

{"feed_id": "...", "xsec_token": "...", "load_all_comments": true, "limit": 20}
  • load_all_comments: false(默认) 返回前10条,true 滚动加载更多
  • limit: 加载评论上限(仅 load_all_comments=true 时生效),默认 20
  • click_more_replies: 是否展开二级回复,默认 false
  • reply_limit: 跳过回复数超过此值的评论,默认 10
  • scroll_speed: slow | normal | fast

post_comment_to_feed — 发表评论

{"feed_id": "...", "xsec_token": "...", "content": "写得真好!"}

reply_comment_in_feed — 回复评论

{"feed_id": "...", "xsec_token": "...", "content": "谢谢!", "comment_id": "...", "user_id": "..."}

comment_id 和 user_id 从 get_feed_detail 返回的评论列表中获取。

user_profile — 用户主页

{"user_id": "...", "xsec_token": "..."}

user_id 从 feed 的 noteCard.user.userId 获取,xsec_token 使用该 feed 的 xsecToken。

like_feed — 点赞/取消

{"feed_id": "...", "xsec_token": "..."}
{"feed_id": "...", "xsec_token": "...", "unlike": true}

favorite_feed — 收藏/取消

{"feed_id": "...", "xsec_token": "..."}
{"feed_id": "...", "xsec_token": "...", "unfavorite": true}

publish_content — 发布图文

{"title": "标题(≤20字)", "content": "正文(≤1000字)", "images": ["/path/to/img.jpg"], "tags": ["美食","旅行"]}
  • images: 至少1张,支持本地路径或 HTTP URL
  • tags: 可选,话题标签
  • schedule_at: 可选,定时发布(ISO8601,1小时~14天内)

publish_with_video — 发布视频

{"title": "标题", "content": "正文", "video": "/path/to/video.mp4"}

其他工具

工具参数说明
check_login_status无检查登录状态
list_feeds无获取首页推荐
get_login_qrcode无获取登录二维码(Base64 PNG)
delete_cookies无删除 cookies,重置登录

热点跟踪

自动搜索 → 拉取详情 → 生成 Markdown 报告。

./track-topic.sh "DeepSeek" --limit 5
./track-topic.sh "春节旅游" --limit 10 --output report.md
./track-topic.sh "iPhone 16" --limit 5 --feishu    # 导出飞书

报告包含:概览统计、热帖详情(正文+热评)、评论关键词、趋势分析。

长图导出

将帖子导出为白底黑字的 JPG 长图。

./export-long-image.sh --posts-file posts.json -o output.jpg

posts.json 格式:

[{
  "title": "标题", "author": "作者", "stats": "1.3万赞",
  "desc": "正文摘要", "images": ["https://..."],
  "per_image_text": {"1": "第2张图的说明"}
}]

依赖:Python 3.10+、Pillow。

注意事项

  • Cookies 有效期约 30 天,过期需重新扫码
  • 首次启动会下载 headless 浏览器(~150MB)
  • 同一账号避免多客户端同时操作
  • 发布限制:标题≤20字符,正文≤1000字符,日发布≤50条
  • Linux 服务器无桌面环境需安装 xvfb(apt-get install xvfb,脚本自动管理)

Score

0–100
66/ 100

Grade

C

Popularity26/30

10,391 installs — strong, widely used.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Xiaohongshu skill score badge previewScore badge

Markdown

[![Xiaohongshu skill](https://www.remoteopenclaw.com/skills/zhjiang22/openclaw-xhs/xiaohongshu/badges/score.svg)](https://www.remoteopenclaw.com/skills/zhjiang22/openclaw-xhs/xiaohongshu)

HTML

<a href="https://www.remoteopenclaw.com/skills/zhjiang22/openclaw-xhs/xiaohongshu"><img src="https://www.remoteopenclaw.com/skills/zhjiang22/openclaw-xhs/xiaohongshu/badges/score.svg" alt="Xiaohongshu skill"/></a>

Xiaohongshu FAQ

How do I install the Xiaohongshu skill?

Run “npx skills add https://github.com/zhjiang22/openclaw-xhs --skill xiaohongshu” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Xiaohongshu skill do?

| The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Xiaohongshu skill free?

Yes. Xiaohongshu is a free, open-source skill published from zhjiang22/openclaw-xhs. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Xiaohongshu work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Xiaohongshu works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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