Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Automate Xiaohongshu (RedNote) content operations using a Python client for the xiaohongshu-mcp server. Use for: (1) Publishing image, text, and video content, (2) Searching for notes and trends, (3) Analyzing post details and comments, (4) Managing user profiles and content feeds. Triggers: xiaohongshu automation, rednote content, publish to xiaohongshu, xiaohongshu search, social media management.
Automate Xiaohongshu (RedNote) content operations using a Python client for the xiaohongshu-mcp server. Use for: (1) Publishing image, text, and video content, (2) Searching for notes and trends, (3) Analyzing post details and comments, (4) Managing user profiles and content feeds. Triggers: xiaohongshu automation, rednote content, publish to xiaohongshu, xiaohongshu search, social media management.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
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
This skill requires the xiaohongshu-mcp server to be running on your local machine.
Download the appropriate binaries for your system from the GitHub Releases page. PlatformMCP ServerLogin ToolmacOS (Apple Silicon)xiaohongshu-mcp-darwin-arm64xiaohongshu-login-darwin-arm64macOS (Intel)xiaohongshu-mcp-darwin-amd64xiaohongshu-login-darwin-amd64Windowsxiaohongshu-mcp-windows-amd64.exexiaohongshu-login-windows-amd64.exeLinuxxiaohongshu-mcp-linux-amd64xiaohongshu-login-linux-amd64 Grant execute permission to the downloaded files: chmod +x xiaohongshu-mcp-darwin-arm64 xiaohongshu-login-darwin-arm64
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.
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.
This skill includes a Python client (scripts/xhs_client.py) to interact with the local server. You can use it directly from the shell.
CommandDescriptionExamplestatusCheck login statuspython scripts/xhs_client.py statussearch <keyword>Search for notespython scripts/xhs_client.py search "咖啡"detail <id> <token>Get note detailspython scripts/xhs_client.py detail "note_id" "xsec_token"feedsGet recommended feedpython scripts/xhs_client.py feedspublish <title> <content> <images>Publish a notepython scripts/xhs_client.py publish "Title" "Content" "url1,url2"
Check Status: First, ensure the server is running and you are logged in. python ~/clawd/skills/xiaohongshu-mcp/scripts/xhs_client.py status 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" 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" Analyze: Review the note's content, comments, and engagement data to gather insights.
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