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Xiaohongshu API MCP Server | 小红书 API 微服务

@proerror77

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

proerror77

About Xiaohongshu API MCP Server | 小红书 API 微服务

XHS MCP Agent - A MCP server implementation

Xiaohongshu API MCP Server | 小红书 API 微服务 config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "xhs_mcp_agent": {
      "command": "python",
      "args": [
        "xhs_api.py"
      ]
    }
  }
}

Xiaohongshu API MCP Server | 小红书 API 微服务 tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Xiaohongshu API MCP Server | 小红书 API 微服务?

Xiaohongshu API MCP Server is a microservice that wraps Xiaohongshu (Little Red Book) API into a RESTful API server, deployable via Docker. It is intended for developers who need programmatic access to Xiaohongshu data.

How to use Xiaohongshu API MCP Server | 小红书 API 微服务?

Build and start the Docker container with docker-compose up -d in the xhs_mcp_server directory, then access the service at http://localhost:8000. Alternatively, run directly with Python after installing dependencies from requirements.txt and executing python xhs_api.py. API documentation is available at /docs (Swagger) or /redoc.

Key features of Xiaohongshu API MCP Server | 小红书 API 微服务

  • RESTful API for Xiaohongshu operations
  • Multiple client instance support
  • Docker containerization for easy deployment
  • Endpoints for notes, users, search, feeds, and health check

Use cases of Xiaohongshu API MCP Server | 小红书 API 微服务

  • Fetching Xiaohongshu notes by ID for content analysis
  • Searching notes and users by keyword for market research
  • Retrieving user information and their posted notes
  • Browsing categorized recommendation feeds for trend monitoring

Frequently asked questions

1

What dependencies are required to run the server?

Docker and Docker Compose are required for containerized deployment. For direct Python running, dependencies are listed in `requirements.txt`.

2

How do I authenticate with the Xiaohongshu API?

Create a client instance by sending a POST request to `/clients` with a JSON body containing your Xiaohongshu cookie.

3

Are there any usage restrictions or data storage details mentioned?

The README states that the project is for educational purposes only (“仅用于教育目的”) and implies use at your own risk. No details about data storage or retention are provided.

4

What transports or authentication mechanisms are supported?

The server exposes HTTP REST endpoints. Authentication is handled via a cookie submitted when creating a client instance; no other transport (e.g., WebSocket) or auth methods (OAuth, tokens) are mentioned.

5

Are there known limits or rate limits?

No limits or rate limits are mentioned in the README.

Comments

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