Search, analyze, and interact with Xiaohongshu (RedNote) content through a unified MCP interface.
Works with
Search notes by keyword with filters (sort, note type, publish time, location); retrieve homepage recommendations and user profiles with associated note lists
Extract complete post details including text, images, interaction metrics, and comment threads; post comments, reply to comments, like, and favorite posts
Publish image or video notes with titles, captions, tags, and optional sched
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionxiaohongshuExecute the skills CLI command in your project's root directory to begin installation:
Fetches xiaohongshu from zhjiang22/openclaw-xhs and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate xiaohongshu. Access via /xiaohongshu in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
2
total installs
2
this week
82
GitHub stars
0
upvotes
Run in your terminal
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installs
2
this week
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stars
基于 xiaohongshu-mcp 封装的 shell 脚本工具集。
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）。
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 | 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 |
{"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{"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 20click_more_replies: 是否展开二级回复，默认 falsereply_limit: 跳过回复数超过此值的评论，默认 10scroll_speed: slow | normal | fast{"feed_id": "...", "xsec_token": "...", "content": "写得真好！"}
{"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_id": "...", "xsec_token": "..."}
user_id 从 feed 的 noteCard.user.userId 获取，xsec_token 使用该 feed 的 xsecToken。
{"feed_id": "...", "xsec_token": "..."}
{"feed_id": "...", "xsec_token": "...", "unlike": true}
{"feed_id": "...", "xsec_token": "..."}
{"feed_id": "...", "xsec_token": "...", "unfavorite": true}
{"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 URLtags: 可选，话题标签schedule_at: 可选，定时发布（ISO8601，1小时~14天内）{"title": "标题", "content": "正文", "video": "/path/to/video.mp4"}
| 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 |
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。
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。
apt-get install xvfb，脚本自动管理）Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
xiaohongshu has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for xiaohongshu matched our evaluation — installs cleanly and behaves as described in the markdown.
xiaohongshu is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in xiaohongshu — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: xiaohongshu is the kind of skill you can hand to a new teammate without a long onboarding doc.
xiaohongshu reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend xiaohongshu for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added xiaohongshu from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: xiaohongshu is focused, and the summary matches what you get after install.
We added xiaohongshu from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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