Book Recommendation MCP Server
Provides personalized book recommendations through OpenRouter and ChatGPT based on user preferences for genres, book length, and topics of interest.
README
Book Recommendation MCP Server
Overview
The Book Recommendation MCP Server is a Node.js-based application designed to provide book recommendations through a simple Model Context Protocol (MCP) interface. It serves both as an educational example of an MCP server implementation and as a foundation for future expansion into a full-featured recommendation system.
The server includes support for static web hosting via the public directory and provides an API endpoint structure that can be extended to include third-party data sources. Future versions will incorporate the Google Books API to enhance recommendations with real-time metadata such as cover images, authors, and descriptions.
Project Objectives
- Implement a functional and extensible MCP server using Node.js and Express.
- Provide a minimal and modular codebase for educational or prototyping purposes.
- Demonstrate integration potential with public APIs, such as Google Books.
- Enable straightforward deployment to cloud hosting platforms such as Render, Railway, or Vercel.
System Architecture
The server follows a lightweight, modular architecture consisting of the following key components:
- server.js – The main application entry point. Initializes Express, defines routes, and serves the frontend.
- public/ – A static directory containing the client-facing HTML and any supporting frontend assets.
- .env – Environment configuration file used to store API keys and other sensitive information.
- package.json – Node.js configuration file specifying dependencies, scripts, and metadata.
- node_modules/ – Automatically generated directory containing project dependencies.
This structure supports the addition of new endpoints and integration layers with minimal refactoring.
Features
- Node.js and Express-based server
- Modular and extendable code design
- Static frontend served from the
/publicdirectory - Example API route for fetching book metadata
- Support for environment variable configuration
- Simple deployment workflow for cloud environments
Setup and Installation
Prerequisites
- Node.js (v18 or later recommended)
- npm (included with Node.js)
Installation Steps
-
Clone the repository:
git clone https://github.com/your-username/book-recommendation-mcp.git cd book-recommendation-mcp
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。