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

1. Check Status: First, ensure the server is running and you are logged in.

   python ~/clawd/skills/xiaohongshu-mcp/scripts/xhs_client.py status

2. 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"

3. 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"

4. Analyze: Review the note's content, comments, and engagement data to gather insights.