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:

1. Open DevTools (F12)
2. Go to Application tab → Cookies → https://www.xiaohongshu.com
3. 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 401 or not_logged_in errors, refresh your cookie
• The server will warn you at startup if XHS_COOKIE is 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.