# VmLia/books-mcp-server [Health: Active]

**Category:** ☁️ Cloud Platforms  
**Repository:** https://github.com/VmLia/books-mcp-server  
**GitHub Stars:** 6  
**Views:** 3  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/vmlia-books-mcp-server

## Description
This is an MCP server used for querying books, and it can be applied in common MCP clients, such as Cherry Studio.

## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):

```json
"mcpServers": {
  "books-mcp-server": {
    "command": "npx",
    "args": ["-y","vmlia-books-mcp-server"]
  }
}
```

## Documentation

## What VmLia/books-mcp-server MCP server does

VmLia/books-mcp-server MCP server exposes book-querying functionality through MCP. Its purpose is narrow: connect an MCP client to a local Python program that can be used to query books. The provided material does not enumerate individual MCP tool names, input fields, result formats, or supported book sources, so those details should be verified in the project code before building client-side workflows around them.

The repository is intended for use with MCP clients that support local stdio processes. Cherry Studio is the documented example. The configuration identifies the server as `books-mcp` and starts the project through `uv`.

## How it works

The project is obtained from GitHub and initialized as a Python environment with `uv`. After dependencies are added, the MCP entry point is run from the project directory using `main.py`. In a client configuration, `uv` receives the project directory, the `run` subcommand, and the Python entry point as arguments.

Communication uses stdio rather than a hosted HTTP endpoint. That means the MCP client starts the process locally and exchanges messages with it through the process input and output streams. The README does not describe a remote deployment mode.

## Setup and configuration

Clone the repository, enter its directory, and create a virtual environment with `uv venv`. Activate the environment with `source .venv/bin/activate` on macOS or Linux, or `.venv\\Scripts\\activate.bat` on Windows.

The documented dependency command adds `mcp[cli]`, `httpx`, `openai`, `beautifulsoup4`, and `lxml`. The README also shows an alternative package index for slower network connections. It does not document environment variables or API keys, so no credential configuration can be confirmed from the supplied material.

In Cherry Studio, add an MCP server with type `STDIO`, set the command to `uv`, and pass these arguments:

- `--directory`
- the local path to the cloned project
- `run`
- `main.py`

The path is installation-specific and must be replaced with the actual checkout location. The same values can be represented in Cherry Studio's JSON configuration under the `mcpServers` object.

## Tools and capabilities

- Query books through an MCP-compatible client.
- Run as a local stdio process.
- Connect to Cherry Studio using its documented MCP server settings.
- Use a `uv`-managed Python environment.

## Limitations and notes

The available description does not list the server's tool names, supported query syntax, data source, ranking behavior, pagination, or response schema. It also does not confirm whether the `openai` dependency is required at runtime or whether a key is needed. Treat those points as implementation details to inspect in the repository rather than assumptions.

VmLia/books-mcp-server MCP server is documented for local execution, not as a hosted service. The Cherry Studio example contains a placeholder project path, so it cannot be copied unchanged into an automated command. No license information is included in the supplied material.

_Full upstream README: https://allmcps.com/mcp/vmlia-books-mcp-server/readme_