xiaohongshu-mcp
Enables AI assistants to interact with Xiaohongshu (Little Red Book) through browser automation, including searching notes, fetching recommendations and details, publishing image-text posts, and liking/favoriting content.
README
@the-thing/xiaohongshu-mcp
小红书 MCP Server（浏览器自动化实现）。扫码登录后，AI 助手可直接搜索笔记、获取推荐/详情、发布图文、点赞收藏。
借鉴 xpzouying/xiaohongshu-mcp 的实现思路（__INITIAL_STATE__ 数据提取、人性化延迟模拟、发布成功验证），采用 Node.js + puppeteer-core 实现，复用本机 Chrome/Edge，无需下载浏览器，npx 一行接入。
安装（一行配置）
在你的 MCP 客户端配置文件（如 ~/.siact/mcps/xiaohongshu.json）中添加：
{
"mcpServers": {
"xiaohongshu": {
"command": "npx",
"args": ["-y", "@the-thing/xiaohongshu-mcp@latest"]
}
}
}
要求：Node.js 18+，本机装有 Google Chrome 或 Microsoft Edge（自动探测，也可用环境变量 PUPPETEER_EXECUTABLE_PATH 指定）。
可用工具（9 个）
| 工具 | 说明 | 必填参数 |
|---|---|---|
xhs_login |
扫码登录小红书（首次使用），登录态自动保存 | 无 |
xhs_check_login |
检查登录状态，返回当前账号昵称 | 无 |
xhs_logout |
退出登录，清除本地登录态 | 无 |
xhs_search_feeds |
按关键词搜索笔记 | keyword, limit? |
xhs_get_recommend_feeds |
获取首页推荐列表 | limit? |
xhs_get_feed_detail |
获取笔记详情（正文/图片/互动/评论） | feedId, xsecToken |
xhs_publish_note |
发布图文笔记（本地图片或 URL） | title, content, images |
xhs_like_feed |
点赞/取消点赞（自动检测状态防重复） | feedId, xsecToken |
xhs_favorite_feed |
收藏/取消收藏（自动检测状态防重复） | feedId, xsecToken |
搜索/推荐结果会返回
id与xsecToken，二者组合才能访问详情页（小红书安全机制），详情/点赞/收藏均需传入。
使用示例
帮我搜索小红书上的"咖啡探店"笔记，取 5 条
→ xhs_search_feeds(keyword="咖啡探店", limit=5)
看一下第一条笔记的详细内容和评论
→ xhs_get_feed_detail(feedId=..., xsecToken=...)
帮我把这张图配一段文案发到小红书：C:\pics\coffee.jpg
→ xhs_publish_note(title="...", content="...", images=["C:\\pics\\coffee.jpg"])
环境变量
| 变量 | 说明 |
|---|---|
PUPPETEER_EXECUTABLE_PATH |
指定 Chrome/Edge 可执行文件路径（默认自动探测） |
XHS_COOKIES_PATH |
登录态 cookies 文件路径（默认 ~/.xiaohongshu-mcp/cookies.json） |
XHS_USER_DATA_DIR |
浏览器 profile 目录（默认临时目录，登录态由 cookies 管理） |
XHS_HEADLESS |
false 时所有操作显示浏览器窗口（默认无头） |
XHS_PROXY |
代理地址（如 http://127.0.0.1:7890） |
本地开发
git clone <repo>
cd xiaohongshu-mcp
npm install
npm start # 启动 MCP server（stdio）
node client.js # 联调：列出工具并调用 xhs_check_login
免责声明
本项目仅用于学习与研究，使用者应遵守小红书平台规则，控制操作频率，账号风险自负。
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.