xiaohongshu — for Claude Code xiaohongshu, oasis7, community, for Claude Code, ide skills, 未登录时需扫码:, 获取二维码,用小红书 App 扫码。 服务端口可通过, 环境变量覆盖(默认, )。 ## 核心数据流 **重要:** 大多数操作需要, search.sh <关键词>

v1.0.0

이 스킬 정보

적합한 상황: Ideal for AI agents that need 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。. 현지화된 요약: xiaohongshu helps AI agents handle repository-specific developer workflows with documented implementation details.

기능

基于 xiaohongshu-mcp 封装的 shell 脚本工具集。
./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。

# Core Topics

eng-cc eng-cc
[2]
[0]
Updated: 4/23/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
46
Canonical Locale
zh
Detected Body Locale
zh

적합한 상황: Ideal for AI agents that need 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。. 현지화된 요약: xiaohongshu helps AI agents handle repository-specific developer workflows with documented implementation details.

이 스킬을 사용하는 이유

추천 설명: xiaohongshu helps agents 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。. xiaohongshu helps AI agents handle repository-specific developer workflows with documented implementation details.

최적의 용도

적합한 상황: Ideal for AI agents that need 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。.

실행 가능한 사용 사례 for xiaohongshu

사용 사례: Applying 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。
사용 사례: Applying ./install-check.sh # 检查依赖(xiaohongshu-mcp、jq、python3)
사용 사례: Applying ./start-mcp.sh # 启动 MCP 服务(默认端口 18060)

! 보안 및 제한 사항

  • 제한 사항: Requires repository-specific context from the skill documentation
  • 제한 사항: Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is xiaohongshu?

적합한 상황: Ideal for AI agents that need 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。. 현지화된 요약: xiaohongshu helps AI agents handle repository-specific developer workflows with documented implementation details.

How do I install xiaohongshu?

Run the command: npx killer-skills add eng-cc/oasis7/xiaohongshu. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for xiaohongshu?

Key use cases include: 사용 사례: Applying 基于 xiaohongshu-mcp 封装的 shell 脚本工具集。, 사용 사례: Applying ./install-check.sh # 检查依赖(xiaohongshu-mcp、jq、python3), 사용 사례: Applying ./start-mcp.sh # 启动 MCP 服务(默认端口 18060).

Which IDEs are compatible with xiaohongshu?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for xiaohongshu?

제한 사항: Requires repository-specific context from the skill documentation. 제한 사항: Works best when the underlying tools and dependencies are already configured.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add eng-cc/oasis7/xiaohongshu. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use xiaohongshu immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

xiaohongshu

Install xiaohongshu, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

小红书 MCP Skill

基于 xiaohongshu-mcp 封装的 shell 脚本工具集。

前置条件

bash
1cd scripts/ 2./install-check.sh # 检查依赖(xiaohongshu-mcp、jq、python3) 3./start-mcp.sh # 启动 MCP 服务(默认端口 18060) 4./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
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
status.sh检查登录
install-check.sh检查依赖

MCP 工具详细参数

search_feeds — 搜索笔记

json
1{"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

json
1{"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

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

reply_comment_in_feed — 回复评论

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

comment_iduser_id 从 get_feed_detail 返回的评论列表中获取。

user_profile — 用户主页

json
1{"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

json
1{"feed_id": "...", "xsec_token": "..."} 2{"feed_id": "...", "xsec_token": "...", "unlike": true}

favorite_feed — 收藏/取消

json
1{"feed_id": "...", "xsec_token": "..."} 2{"feed_id": "...", "xsec_token": "...", "unfavorite": true}

publish_content — 发布图文

json
1{"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

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

其他工具

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

热点跟踪

自动搜索 → 拉取详情 → 生成 Markdown 报告。

bash
1./track-topic.sh "DeepSeek" --limit 5 2./track-topic.sh "春节旅游" --limit 10 --output report.md 3./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。

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

posts.json 格式:

json
1[{ 2 "title": "标题", "author": "作者", "stats": "1.3万赞", 3 "desc": "正文摘要", "images": ["https://..."], 4 "per_image_text": {"1": "第2张图的说明"} 5}]

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)

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