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Azure Container Apps - AI & MCP Playground

@manekinekko

リポジトリ

基本情報

カテゴリ

クラウドとインフラ

ライセンス

MIT

トランスポート

stdio

作者

manekinekko

Azure Container Apps - AI & MCP Playground について

This project showcases how to use the MCP protocol with Azure OpenAI. It provides a simple example to interact with OpenAI's API seamlessly via an MCP server and client.

#azure#mcp#openai#agents#llm

Azure Container Apps - AI & MCP Playground 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": {
    "azure-openai-mcp-example": {
      "command": "docker",
      "args": [
        "compose",
        "up",
        "-d",
        "--build"
      ]
    }
  }
}

Azure Container Apps - AI & MCP Playground 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 Azure Container Apps - AI & MCP Playground?

This demo application showcases the MCP protocol with OpenAI, Azure OpenAI, and GitHub Models. It provides a terminal application that interacts with a TODO list agent using tools from an MCP server, intended for developers exploring AI agent integration.

How to use Azure Container Apps - AI & MCP Playground?

Clone the repository and run docker-compose up to start containers. Alternatively, install dependencies with npm install per prefix and run npm start --prefix mcp-server-http, mcp-server-sse, and mcp-host in separate terminals. Configure the LLM provider via a .env file with keys like OPENAI_API_KEY, AZURE_OPENAI_ENDPOINT, or GITHUB_TOKEN.

Key features of Azure Container Apps - AI & MCP Playground

  • Supports SSE and HTTP streaming MCP servers
  • Integrates with OpenAI, Azure OpenAI, GitHub Models
  • Uses DocumentDB Local for state persistence
  • Provides tools for TODO list management
  • Docker Compose for easy setup
  • Configurable debug logging via DEBUG env variable

Use cases of Azure Container Apps - AI & MCP Playground

  • Build a terminal-based AI assistant with tool access
  • Experiment with MCP protocol using different LLM providers
  • Develop and test MCP server implementations
  • Explore integration of AI agents with persistent database storage

よくある質問

1

How does this server differ from other MCP servers?

This playground focuses on demonstrating MCP with multiple LLM providers and includes both HTTP and SSE transport, a local database, and a host application.

2

What are the runtime dependencies?

Node.js 22+, Docker, and an OpenAI compatible endpoint (OpenAI API key, GitHub token, or Azure OpenAI endpoint).

3

Where is agent state stored?

State is stored in DocumentDB Local, a lightweight database running in Docker.

4

Does it support authentication?

Authentication is a work in progress; currently no token-based auth for the MCP servers.

5

How can I debug the MCP host?

Set the `DEBUG` environment variable to `mcp:*` before starting the host.

コメント

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