Gen AI Lyrics Search Agent

Gen AI Lyrics Search Agent

A generative AI agent that searches song lyrics across the web and returns results formatted for mobile apps, built with MCP.

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README

Gen AI Lyrics Search Agent

A generative AI agent that can search for song lyrics across the web and return results in a specific format for mobile apps. Built with Model Context Protocol (MCP) for standardized tool integration.

Features

  • šŸ” Web-based lyrics search across multiple sources
  • šŸ¤– Generative AI-powered conversation interface
  • šŸ”Œ MCP-compliant tool integration
  • šŸš€ FastAPI-based REST API
  • šŸ”’ Authentication and rate limiting
  • šŸ“Š Performance monitoring and analytics

Prerequisites

  • Python 3.10 or higher
  • Poetry for dependency management
  • Docker (optional)

Setup

  1. Clone the repository:
git clone <repository-url>
cd lyrics-search-agent
  1. Install dependencies using Poetry:
poetry install
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your configuration
  1. Run the application:
poetry run uvicorn app.main:app --reload

Or using Docker:

docker build -t lyrics-search-agent .
docker run -p 8000:8000 lyrics-search-agent

API Documentation

Once the application is running, visit:

  • API documentation: http://localhost:8000/docs
  • ReDoc alternative: http://localhost:8000/redoc

Key Endpoints

  • GET /: Service information
  • POST /search: Search for lyrics
  • GET /tools: List available tools

Development

Project Structure

app/
ā”œā”€ā”€ __init__.py
ā”œā”€ā”€ main.py
ā”œā”€ā”€ mcp/
│   ā”œā”€ā”€ __init__.py
│   └── protocol.py
└── tools/
    └── web_search.py

Adding New Tools

  1. Create a new tool class in app/tools/
  2. Implement the BaseTool interface
  3. Register the tool in app/main.py

Testing

Run tests using pytest:

poetry run pytest

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • OpenAI/Anthropic for LLM capabilities
  • FastAPI for the web framework
  • LangChain for LLM orchestration

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