Library Assistant

A conversational AI assistant that helps users discover books using the Open Library API. Built with LangChain, Gradio, and the Model Context Protocol (MCP).

Features

• Book Search: Search for books by title, author, or keywords
• Author Search: Find authors and explore their works
• Subject Browsing: Browse books by genre/subject (fantasy, romance, mystery, etc.)
• Book Recommendations: Get personalized book recommendations based on interests
• Conversational Interface: Natural language chat interface powered by GPT-4o-mini

Technologies Used

Technology	Purpose
Python	Programming language
Gradio	Chat UI framework
LangChain	AI agent framework
MCP (Model Context Protocol)	Tool communication protocol
FastMCP	MCP server implementation
OpenRouter	LLM API provider
Open Library API	Book data source
httpx	HTTP client for API requests

Prerequisites

• Python 3.10 or higher
• An OpenRouter API key

Installation

1. Clone the repository:

   git clone https://github.com/fernandovbs/library-assistant.git
   cd library-assistant

2. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Configure environment variables:

   Copy the example environment file and add your API key:

   cp example.env .env

   Edit .env and set your OpenRouter API key:

   OPENROUTER_API_KEY=your_api_key_here
   OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
   

Running the Application

The application consists of two components that need to be run in separate terminals:

1. Start the MCP Server

In the first terminal:

python mcp_server.py

The server will start at http://localhost:8000 with the SSE endpoint at http://localhost:8000/sse.

2. Start the Chat Application

In a second terminal:

python chat_app_mcp.py

The Gradio interface will open in your browser (typically at http://127.0.0.1:7860).

Usage

Once both servers are running, you can interact with the assistant through the chat interface. Try questions like:

• "Recommend me a good science fiction book"
• "Search for books by Isaac Asimov"
• "Show me popular mystery novels"
• "Find books about artificial intelligence"
• "What are the top fantasy books?"

Available Tools

The MCP server exposes the following tools:

Tool	Description
search_books	Search for books by title, author, or keywords
search_authors	Search for authors and see their works
browse_subject	Browse books by subject/genre
get_author_works	Get all works by a specific author using their Open Library ID
recommend_books	Get book recommendations based on interests

Project Structure

library-assistant/
├── chat_app_mcp.py    # Gradio chat application with LangChain agent
├── mcp_server.py      # MCP server with Open Library tools
├── requirements.txt   # Python dependencies
├── example.env        # Example environment variables
├── .env               # Your environment variables (not in git)
└── README.md          # This file

Configuration

Environment Variables

Variable	Description	Default
OPENROUTER_API_KEY	Your OpenRouter API key	Required
OPENROUTER_BASE_URL	OpenRouter API base URL	https://openrouter.ai/api/v1
MCP_SERVER_URL	MCP server SSE endpoint	http://localhost:8000/sse

License

This project uses the Open Library API for book data.

Acknowledgments

• Open Library for providing free book data
• LangChain for the AI agent framework
• Gradio for the chat interface
• Model Context Protocol for tool communication