Xiaohongshu MCP Skill (with Python Client)
Automate content operations on Xiaohongshu (小红书) using a bundled Python script that interacts with the xpzouying/xiaohongshu-mcp server (8.4k+ stars).
Project: xpzouying/xiaohongshu-mcp
1. Local Server Setup
This skill requires the xiaohongshu-mcp server to be running on your local machine.
Step 1: Download Binaries
Download the appropriate binaries for your system from the GitHub Releases page.
Grant execute permission to the downloaded files:
chmod +x xiaohongshu-mcp-darwin-arm64 xiaohongshu-login-darwin-arm64
Step 2: Login (First Time Only)
Run the login tool. It will open a browser window with a QR code. Scan it with your Xiaohongshu mobile app.
./xiaohongshu-login-darwin-arm64
Important: Do not log into the same Xiaohongshu account on any other web browser, as this will invalidate the server's session.
Step 3: Start the MCP Server
Run the MCP server in a separate terminal window. It will run in the background.
# Run in headless mode (recommended)
./xiaohongshu-mcp-darwin-arm64
# Or, run with a visible browser for debugging
./xiaohongshu-mcp-darwin-arm64 -headless=false
The server will be available at http://localhost:18060.
2. Using the Skill
This skill includes a Python client (scripts/xhs_client.py) to interact with the local server. You can use it directly from the shell.
Available Commands
Example Workflow: Market Research
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Check Status: First, ensure the server is running and you are logged in.
python ~/clawd/skills/xiaohongshu-mcp/scripts/xhs_client.py status
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Search for a Keyword: Find notes related to your research topic. The output will include the feed_id and xsec_token needed for the next step.
python ~/clawd/skills/xiaohongshu-mcp/scripts/xhs_client.py search "户外电源"
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Get Note Details: Use the feed_id and xsec_token from the search results to get the full content and comments of a specific note.
python ~/clawd/skills/xiaohongshu-mcp/scripts/xhs_client.py detail "64f1a2b3c4d5e6f7a8b9c0d1" "security_token_here"
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Analyze: Review the note's content, comments, and engagement data to gather insights.