xhs-mcp
A lightweight MCP server that provides read-only access to Xiaohongshu (Little Red Book) data, enabling search, note details, user profiles, and trending feeds via direct HTTP APIs.
README
xhs-mcp
Lightweight MCP server for Xiaohongshu (Little Red Book / RED) — China's #1 lifestyle platform with 300M+ monthly active users.
No Docker. No Chromium. Just npx.
npx xhs-mcp-server
Why this exists
Xiaohongshu (小红书) is where Chinese consumers discover products, share reviews, and follow trends. If you're building for the Chinese market — or just want to understand what's trending there — you need data from this platform.
Existing solutions require Docker + Chromium (heavy, fragile). This server uses direct HTTP APIs, so it starts in <1 second and works anywhere Node.js runs.
What you can do
| Tool | Description |
|---|---|
xhs_search |
Search notes by keyword with sorting and filtering |
xhs_note_detail |
Get full content, images, and metrics for any note |
xhs_user_profile |
Get creator profiles with follower/engagement stats |
xhs_user_notes |
List all notes from a specific creator |
xhs_explore |
Get the current trending/recommended feed |
Quick start
1. Get your cookie
Log in to xiaohongshu.com in Chrome, then:
- Open DevTools (
F12) - Go to Application tab → Cookies →
https://www.xiaohongshu.com - Copy the entire cookie string (or use a browser extension like "EditThisCookie" to export)
2. Add to your AI tool
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"xhs": {
"command": "npx",
"args": ["-y", "xhs-mcp-server"],
"env": {
"XHS_COOKIE": "your_cookie_string_here"
}
}
}
}
Cursor (.cursor/mcp.json):
{
"mcpServers": {
"xhs": {
"command": "npx",
"args": ["-y", "xhs-mcp-server"],
"env": {
"XHS_COOKIE": "your_cookie_string_here"
}
}
}
}
Claude Code:
claude mcp add xhs -- npx -y xhs-mcp-server
# Then set XHS_COOKIE in your environment
3. Use it
Ask your AI assistant:
- "Search Xiaohongshu for skincare trends"
- "Find the top creators posting about coffee in Shanghai"
- "What's trending on Xiaohongshu right now?"
- "Analyze this Xiaohongshu creator's content strategy"
Use cases
For cross-border brands:
- Monitor brand mentions and competitor activity on China's top discovery platform
- Understand what products Chinese consumers are excited about
- Find potential KOL/KOC partners by analyzing creator profiles and engagement
For market researchers:
- Track trending topics and consumer sentiment in China
- Analyze content strategies that work on Xiaohongshu
- Discover emerging product categories before they hit Western markets
For developers:
- Build Chinese market intelligence into your AI agents
- Create automated competitor monitoring dashboards
- Integrate Xiaohongshu data into your workflow
How it compares
| Feature | xhs-mcp (this) | xpzouying/xiaohongshu-mcp |
|---|---|---|
| Language | TypeScript/Node | Go |
| Install | npx (1 second) |
Docker + Chromium (minutes) |
| Dependencies | None | Docker, Chromium, ~500MB |
| Search | Yes | Yes |
| Read notes | Yes | Yes |
| User profiles | Yes | Yes |
| Publish content | Not yet | Yes |
| Login (QR code) | Not yet | Yes |
| Auth method | Cookie (manual) | Browser automation |
This server is read-only by design. It focuses on research and analysis. If you need to publish content, use xpzouying/xiaohongshu-mcp — it's excellent for that.
Cookie notes
- Cookies typically last 7-30 days before expiring
- If you get
401ornot_logged_inerrors, refresh your cookie - The server will warn you at startup if
XHS_COOKIEis not set - Never commit your cookie to version control
Roadmap
- [ ] Creator analytics (engagement rate calculation, posting frequency)
- [ ] Comment analysis (sentiment, themes)
- [ ] Trend detection (rising keywords over time)
- [ ] Content translation (Chinese → English summaries)
- [ ] Cookie refresh helper
- [ ] Publish support (opt-in, with rate limiting)
Contributing
PRs welcome. This project is MIT licensed.
About
Built by Tristin — building AI tools for cross-border commerce, in public.
Xiaohongshu is a trademark of Xingyin Information Technology Co., Ltd. This project is not affiliated with or endorsed by Xiaohongshu.
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