关于
This project provides a YouTube search application designed to demonstrate three distinct methods for accessing and searching YouTube content. It serves as an educational resource and reference implementation, showcasing direct Flask app integration with the YouTube Data API, a dedicated MCP server for structured search, and a Flask client that consumes the MCP server. While not intended for production use, it is an excellent tool for developers to understand MCP concepts, explore different architectural patterns for API interaction, and integrate YouTube search capabilities into AI clients like Claude Code or Gemini CLI.
主要功能
- Three distinct implementation approaches (Direct Flask, MCP Server, Flask + MCP client)
- Search videos, channels, and playlists via YouTube Data API
- Model Context Protocol (MCP) implementation for structured search
- Web interfaces and JSON API endpoints for each approach
- Integration examples for AI clients (Claude Code, Gemini CLI)
- 0 GitHub stars
使用案例
- Integrating YouTube search functionality with AI assistants or agents
- Learning and demonstrating Model Context Protocol (MCP) concepts
- Experimenting with different architectural patterns for API interactions in Python
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