Skip to content
Dhanasvi
Sign inExplore
Xiaohongshu logo

Xiaohongshu

Verified

MCP server for accessing and posting to Xiaohongshu (Little Red Book).

MCP ServerOtherLocal (stdio) 14.2k
View on GitHub
Updated 2026-06-15

What is the Xiaohongshu MCP server?

The server implements 11 core operations including login, publishing notes and videos, searching content, retrieving recommendations and post details, commenting, replying, liking, favoriting, and fetching user profiles. All actions require prior login and often use feed_id plus xsec_token obtained from search or feed results.

It supports both HTTP image URLs and local file paths for uploads, enforces Xiaohongshu limits such as 20-character titles, and provides detailed interaction data and comment trees when fetching posts.

Install & connect

Add this to your MCP client config. Pick your client below and copy.

{
  "mcpServers": {
    "xiaohongshu-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/inspector"
      ]
    }
  }
}

Package: @modelcontextprotocol/inspector (npm)

Other ways to install

npx

npx
npx -y @modelcontextprotocol/inspector

Tools it exposes

12 tools your AI client can call once connected.

login— Login to Xiaohongshu account
check_login_status— Check current login status
publish_image_note— Publish image-text content with title, description and images
titlecontentimages
publish_video_note— Publish video content with title, description and local video path
titlecontentvideo_path
search_notes— Search Xiaohongshu content by keywords
keyword
get_recommendations— Get homepage recommended content list
get_note_detail— Get full post details including comments and interaction data
feed_idxsec_token
comment_on_note— Post a comment to a note
feed_idxsec_tokencontent
get_user_profile— Get user homepage information and notes
user_idxsec_token
reply_to_comment— Reply to a specific comment on a note
feed_idxsec_tokencomment_idcontent
like_note— Like or unlike a note
feed_idxsec_tokenunlike
favorite_note— Favorite or unfavorite a note
feed_idxsec_tokenunfavorite

Example prompts

Once connected, try asking your AI client:

“Search Xiaohongshu for latest travel notes about Kyoto
“Publish a new note with title 'Best cafes in Shanghai' and two local images
“Get details and comments for feed_id 12345 with its xsec_token
“Like the note with feed_id abc and xsec_token xyz

Security & permissions

Runs locally via stdio and requires a logged-in Xiaohongshu session; touches local image/video files and account credentials during use.

What you can do with Xiaohongshu

Content publishing automation

Publish image or video notes with titles, descriptions, and local media files directly from an AI workflow.

Social listening and research

Search keywords, fetch recommendations, and retrieve full post details including comments and engagement metrics.

Engagement management

Comment on posts, reply to specific comments, like or favorite notes after authenticating with a user account.

How to use Xiaohongshu

  1. 1Clone the xpzouying/xiaohongshu-mcp repository and install dependencies.
  2. 2Run the server using Docker or directly with Node.js via stdio.
  3. 3Configure your AI client to connect to the stdio MCP server.
  4. 4Use the login tool first, then obtain feed_id and xsec_token from search or recommendations.
  5. 5Call publish, comment, or other tools with required parameters.

Xiaohongshu: pros & cons

Pros

  • +Comprehensive coverage of Xiaohongshu actions including video upload and comment replies
  • +Supports both remote image URLs and stable local file paths
  • +Detailed parameter guidance and demo videos in documentation
  • +Active maintenance with donation tracking and contributor badges

Cons

  • –Requires manual login step and xsec_token for most read/write operations
  • –Only local video files supported; no remote video URLs
  • –Deployment can be complex without the alternative browser plugin
Did you find this helpful?

Frequently asked questions

Yes, the login tool must be called first and login status should be verified.

User reviews

Verified reviews from the community shape this listing's rating.

Loading reviews…

Sign in to review

Promote Xiaohongshu

Add this badge to your website, or share the tool.

DFeatured on DhanasviXiaohongshu 1