books

This MCP server runs a Python-based project that exposes a console-driven interface via the Standard Input/Output (STDIO) protocol using the uv runner. The server relies on a local Python environment with the mcp CLI tooling installed, and it executes the main entry point (main.py) of the books-mcp-server project. To interact, you typically configure the server in a GUI like cherry-studio or feed the same configuration programmatically, enabling you to start, monitor, and pass messages to the running MCP application. The included configuration demonstrates invoking uv with a directory pointing to your local project and running main.py, which allows the MCP protocol to manage request/response interactions through standard I/O.

Prerequisites

• Python 3.8+ installed on your system
• Access to the internet to install Python packages
• git installed to clone the repository

Step 1: Clone the repository

git clone https://github.com/VmLia/books-mcp-server.git
cd books-mcp-server

Step 2: Create and activate a Python virtual environment (recommended)

• macOS/Linux

uv venv
source .venv/bin/activate

• Windows

uv venv
.venv\Scripts\activate.bat

Step 3: Install required Python packages (MCP CLI and dependencies)

uv add "mcp[cli]" httpx openai beautifulsoup4 lxml

Optional: If you are behind a slow network, you can use a domestic mirror for PyPI

uv add "mcp[cli]" httpx openai beautifulsoup4 lxml --index-url https://pypi.tuna.tsinghua.edu.cn/simple

Step 4: Run or configure the MCP server

• You can run using the STDIO method via cherry-studio or any MCP client that supports STDIO, using the command and arguments shown in the README configuration.

uv --directory /Enter your local project directory/books-mcp-server run main.py

Step 5: Verify operation

• Ensure the directory path is correct and main.py is present.
• Check for any import or package errors in the console output and install missing dependencies if necessary.

Tips and notes:

• The server uses STDIO via the uv runner; ensure the directory path in the configuration exactly points to your local books-mcp-server project.
• If you encounter import errors, verify that the virtual environment is activated and that all required packages (mcp[cli], httpx, openai, beautifulsoup4, lxml) are installed.
• You can mirror PyPI to speeds up installs in restricted networks by using the provided --index-url option.
• For GUI integrations (e.g., cherry-studio), follow the Type and Command shown in the example: Type STDIO and Command uv, with parameters to run main.py from your project directory.
• If you modify main.py or the directory structure, update the args accordingly in your MCP configuration.
• This server does not publish a public npm package; it is Python-based.