MCP V4x

🚀 WeRead Model Context Protocol Server (MCP Server)

This is a tool designed to interact with the WeRead API, aiming to assist Large Language Model (LLM) clients in retrieving and processing data from WeRead. The tool supports the following features:

• Retrieve the user's bookshelf information.
• Search for books in specific categories.
• Obtain notes and highlights from a specified book.

✨ Features

1. Get Bookshelf Information (get_bookshelf)

• Function Description: Returns information about all books under the user's WeRead account, including the book title, author, reading progress, etc.
• Sample Output:

  {
    "total_books": 208,
    "books": [
      {
        "title": "The Hidden Self",
        "author": "David Eagleman",
        "progress": 100,
        "isbn": "9787536684455"
      },
      ...
    ]
  }
  

2. Search for Books (search_books)

• Function Description: Searches for books in the bookshelf based on keywords, supporting fuzzy matching.
• Input Parameters:
  • keyword: The keyword to search for.
  • max_results (optional): The maximum number of results to return, default is 10.
• Sample Output:

  [
    {
      "title": "Thinking, Fast and Slow",
      "author": "Daniel Kahneman",
      "progress": 75,
      "isbn": "9787208056432"
    },
    ...
  ]
  

3. Get Notes and Highlights (get_book_notes_and_highlights)

• Function Description: Returns the notes and highlights of a specified book, organized by chapter.
• Input Parameters:
  • book_id: The ID of the book to query.
• Sample Output:

  {
    "chapter_1": [
      {
        "type": "highlight",
        "content": "System 1 operates automatically and quickly, with little or no effort..."
      },
      {
        "type": "note",
        "content": "System 1 is responsible for intuition and quick judgments, while System 2 is responsible for slow, deliberate thinking."
      }
    },
    ...
  }
  

📦 Installation

Prerequisites

• Operating Systems: Linux, Windows, macOS are supported.
• Dependencies:
  • Python >=3.6
  • requests library
  • configargparse library

Installation Steps

1. Clone the code repository to your local machine:

   git clone https://github.com/yourusername/we-read-mcp.git
   cd we-read-mcp
   

2. Install the dependencies:

   pip install requests configargparse
   

3. Configure environment variables or create a configuration file (see below).
4. Run the main program:

   python main.py
   

Environment Variable Configuration

You can configure it in the following ways:

• Method 1: Edit config.json

  {
    "cookie": "Fill in your WeRead Cookie",
    "proxy": "http://your-proxy-server:port"
  }
  

• Method 2: Set environment variables

  export WEREAD_COOKIE="Fill in your WeRead Cookie"
  export WEREAD_PROXY="http://your-proxy-server:port"
  

💻 Usage Examples

Example 1 - Get Bookshelf Information

python main.py --command get_bookshelf

Output:

{
  "total_books": 208,
  "books": [
    {
      "title": "The Hidden Self",
      "author": "David Eagleman",
      "progress": 100,
      "isbn": "9787536684455"
    },
    ...
  ]
}

Example 2 - Search for Books

python main.py --command search_books --keyword "Psychology" --max_results 5

Output:

[
  {
    "title": "Thinking, Fast and Slow",
    "author": "Daniel Kahneman",
    "progress": 75,
    "isbn": "9787208056432"
  },
  ...
]

Example 3 - Get Notes and Highlights

python main.py --command get_book_notes_and_highlights --book_id "9787208056432"

Output:

{
  "chapter_1": [
    {
      "type": "highlight",
      "content": "System 1 operates automatically and quickly, with little or no effort..."
    },
    {
      "type": "note",
      "content": "System 1 is responsible for intuition and quick judgments, while System 2 is responsible for slow, deliberate thinking."
    }
  },
  ...
}

📚 Documentation

Important Notes

• You need to obtain a valid WeRead Cookie to use this tool.
• If you need to use a proxy, ensure that the proxy information is correctly configured.
• Please comply with WeRead's terms of service during use.

📄 License

This project is open-sourced under the MIT License.