xiaohongshu-wiki/.agents/skills/xiaohongshu

XHS AI Toolkit

Make AI understand your Xiaohongshu (RedNote)

简体中文 | English

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AI-powered toolkit for Xiaohongshu (小红书 / RedNote) that turns your favorite posts into AI memory.

• MCP Integration — Search, browse, comment via AI assistants
• Trend Tracking — Auto-generate topic reports with engagement analytics
• Memory Export — Convert your liked/saved posts into AI-searchable knowledge base

Built on xiaohongshu-mcp and XHS-Downloader.

Features

Feature	Description
Search	Search posts by keywords
Feed	Get homepage recommendations
Post Details	Fetch post content, comments, engagement stats
Comment	Post comments to notes
User Profile	Get user info and their posts
Trend Tracking	Auto-generate topic analysis reports
Long Image Export	Export posts as annotated JPG long images
Memory Export	Export liked/saved posts as Markdown for AI memory

Quick Start

1. Install xiaohongshu-mcp

Download from GitHub Releases:

# Linux x64
wget https://github.com/xpzouying/xiaohongshu-mcp/releases/latest/download/xiaohongshu-mcp-linux-amd64.tar.gz
wget https://github.com/xpzouying/xiaohongshu-mcp/releases/latest/download/xiaohongshu-login-linux-amd64.tar.gz

# macOS ARM
wget https://github.com/xpzouying/xiaohongshu-mcp/releases/latest/download/xiaohongshu-mcp-darwin-arm64.tar.gz
wget https://github.com/xpzouying/xiaohongshu-mcp/releases/latest/download/xiaohongshu-login-darwin-arm64.tar.gz

Install:

mkdir -p ~/.local/bin
tar -xzf xiaohongshu-mcp-*.tar.gz -C ~/.local/bin/
tar -xzf xiaohongshu-login-*.tar.gz -C ~/.local/bin/

cd ~/.local/bin
mv xiaohongshu-mcp-* xiaohongshu-mcp
mv xiaohongshu-login-* xiaohongshu-login
chmod +x xiaohongshu-mcp xiaohongshu-login

2. Install This Toolkit

# Clone to OpenClaw workspace
git clone https://github.com/zhjiang22/openclaw-xhs.git
cp -r openclaw-xhs ~/.openclaw/workspace/skills/xiaohongshu

# Or use symlink
ln -s /path/to/openclaw-xhs ~/.openclaw/workspace/skills/xiaohongshu

# Verify installation
cd ~/.openclaw/workspace/skills/xiaohongshu/scripts
./install-check.sh

3. Login (Get Cookies)

Option A: Desktop Environment

./login.sh  # Opens browser, scan QR code with Xiaohongshu app

Option B: Headless Server

Get cookies on your local machine, then copy to server:

# On local machine with GUI
./xiaohongshu-login
# Cookies saved to /tmp/cookies.json

# Copy to server
scp /tmp/cookies.json user@server:~/.xiaohongshu/cookies.json

4. Start Service

./start-mcp.sh              # Headless mode
./start-mcp.sh --headless=false  # Show browser (debug)

Service runs at http://localhost:18060/mcp.

Server Deployment (Headless Linux)

On servers without a desktop environment, the underlying browser requires a virtual display. start-mcp.sh auto-detects the environment — if no display is found, it starts Xvfb automatically. Just install it first:

# Debian/Ubuntu
sudo apt-get install -y xvfb

# CentOS/RHEL
sudo yum install -y xorg-x11-server-Xvfb

No extra configuration needed. The script handles:

• Detecting the DISPLAY environment variable
• Auto-starting Xvfb :99 when no display is available
• Cleaning up Xvfb when stop-mcp.sh is called

Note

: Without Xvfb, login and search will fail on headless servers. See Issue #3.

Usage

Basic Commands

./status.sh                    # Check login status
./search.sh "coffee"           # Search posts
./recommend.sh                 # Get recommendations
./post-detail.sh <id> <token>  # Get post details
./comment.sh <id> <token> "Great post!"  # Comment
./user-profile.sh <user_id> <xsec_token>  # Get user profile

Trend Tracking

Auto-search trending posts and generate analysis reports:

./track-topic.sh "AI" --limit 10
./track-topic.sh "travel" --limit 5 --output report.md
./track-topic.sh "iPhone" --limit 5 --feishu  # Export to Feishu

MCP Tools

Tool	Description
check_login_status	Check login status
search_feeds	Search posts
list_feeds	Get homepage feed
get_feed_detail	Get post details & comments
post_comment_to_feed	Post comment
user_profile	Get user profile
like_feed	Like/unlike post
favorite_feed	Save/unsave post
publish_content	Publish image post
publish_with_video	Publish video post

Long Image Export

Export posts as annotated JPG long images (white background, black text):

# Prepare posts.json
cat > posts.json << 'EOF'
[
  {
    "title": "Post title",
    "author": "Author",
    "stats": "13k likes 100 saves",
    "desc": "Post summary",
    "images": ["https://...webp"],
    "per_image_text": {"1": "Caption for 2nd image"}
  }
]
EOF

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

Requires: Python 3.10+, Pillow (pip install Pillow)

Memory Export (Turn Likes into AI Memory)

Export your liked/saved posts as a searchable knowledge base for AI assistants.

1. Install XHS-Downloader

git clone https://github.com/JoeanAmier/XHS-Downloader.git
cd XHS-Downloader
pip install -r requirements.txt

2. Extract Post Links (Tampermonkey Script)

1. Install Tampermonkey
2. Install XHS-Downloader UserScript
3. Go to Xiaohongshu web → Profile → Liked/Saved
4. Click Tampermonkey menu → "Extract liked posts" or "Extract saved posts"
5. Links auto-copied to clipboard
6. Paste into links.md

3. Download & Export

# Copy helper scripts
cp tools/xhs-downloader/*.py /path/to/XHS-Downloader/

# Download posts
cd /path/to/XHS-Downloader
python batch_download.py links.md

# Export to workspace
python export_to_workspace.py
# Output: ~/.openclaw/workspace/xhs-memory/

4. Configure OpenClaw Memory Search

Edit ~/.openclaw/openclaw.json:

{
  "memorySearch": {
    "extraPaths": [
      "~/.openclaw/workspace/xhs-memory"
    ]
  }
}

Now your AI assistant can search your Xiaohongshu favorites!

Project Structure

openclaw-xhs/
├── README.md             # English docs
├── README_CN.md          # Chinese docs
├── LICENSE
├── SKILL.md              # Skill manifest
├── scripts/              # MCP wrapper scripts
│   ├── install-check.sh
│   ├── start-mcp.sh
│   ├── stop-mcp.sh
│   ├── login.sh
│   ├── mcp-call.sh
│   ├── status.sh
│   ├── search.sh
│   ├── recommend.sh
│   ├── post-detail.sh
│   ├── comment.sh
│   ├── user-profile.sh
│   ├── track-topic.sh
│   ├── track-topic.py
│   ├── export-long-image.sh
│   └── export-long-image.py
└── tools/
    └── xhs-downloader/   # Memory export tools
        ├── README.md
        ├── batch_download.py
        ├── export_memory.py
        └── export_to_workspace.py

Security

This project implements the following security measures:

• Cookie protection: Cookie files are copied with 600 permissions (owner-only read/write)
• Injection prevention: All shell scripts use jq to build JSON payloads instead of string interpolation, preventing shell injection
• Tool name validation: MCP tool names are restricted to alphanumeric characters and underscores
• Path validation: Cross-skill script calls validate that target paths are within allowed directories
• Third-party content: Content fetched from Xiaohongshu is user-generated; exercise appropriate caution

Disclaimer

This project is a wrapper layer for xiaohongshu-mcp.

• Does NOT contain xiaohongshu-mcp source code
• Users must download xiaohongshu-mcp binaries separately
• Scripts communicate via HTTP protocol only

Acknowledgments

• @xpzouying — xiaohongshu-mcp
• @JoeanAmier — XHS-Downloader (GPL-3.0)

License

MIT License (wrapper scripts only)

Note: xiaohongshu-mcp has no declared license. Please respect the author's terms.

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