YouTube Search Assistant with ADK, MCP and Gemma 3

@arjunprabhulal

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基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

arjunprabhulal

YouTube Search Assistant with ADK, MCP and Gemma 3 について

Build AI Agent using Google ADK , MCP and Gemma 3 model

#mcp#google-cloud-platform#youtube-search#adk#ollama #mcp-server #mcp-client#gemma3

YouTube Search Assistant with ADK, MCP and Gemma 3 の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "adk-mcp-gemma3": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

YouTube Search Assistant with ADK, MCP and Gemma 3 のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is YouTube Search Assistant with ADK, MCP and Gemma 3?

A practical implementation demonstrating YouTube search functionality using Google's Agent Development Kit (ADK), Model Context Protocol (MCP), and the Gemma 3 model hosted locally via Ollama. It creates a conversational agent that can search YouTube, format results, and respond in natural language.

How to use YouTube Search Assistant with ADK, MCP and Gemma 3?

Clone the repository, install dependencies, set up a .env file with your SERP API key, and pull the Gemma 3 model with Ollama. Then run adk web for a browser-based UI or python -m search for command‑line interaction. Example queries include “Find videos about Google Cloud Next 25” or “Search for YouTube tutorials on Python programming.”

Key features of YouTube Search Assistant with ADK, MCP and Gemma 3

Search for YouTube videos using natural language queries
Powered by Gemma 3 running locally on Ollama
Formats search results in a clean, easy-to-read format
Built with Google’s Agent Development Kit (ADK)
Integrates Model Context Protocol (MCP) for tool communication
Uses SERP API to access YouTube data

Use cases of YouTube Search Assistant with ADK, MCP and Gemma 3

Find videos about specific events (e.g., Google Cloud Next 25)
Search for YouTube tutorials on programming languages
Look for educational videos on machine learning topics
Create a conversational assistant for video discovery

よくある質問

What are the runtime requirements?

Python 3.9+, Ollama installed with the Gemma 3 model, and a SERP API key for YouTube search.

How do I set up the SERP API key?

Create a `.env` file in the project root directory with the line `SERP_API_KEY=your_serp_api_key_here`.

What if the model doesn’t use tools properly?

Ensure your query clearly requires external information. You can also try making the tool description more explicit in the agent configuration.

What should I do if I encounter a LiteLLM/Ollama KeyError?

This is a known bug caused by Ollama’s JSON format responses and LiteLLM’s parsing. Workarounds include manually patching LiteLLM with the changes from PR #9966 or avoiding `format=json` in requests.

What if I have memory constraints?

The 12B model requires significant RAM/VRAM. Consider using a smaller model like `gemma3:7b` or `gemma3:1b` if you experience memory issues.

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