OpenAI MCP Example

@manekinekko

リポジトリ

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

manekinekko

OpenAI MCP Example 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.

#mcp #openai #agents #llm

OpenAI MCP Example 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": {
    "openai-mcp-example": {
      "command": "docker",
      "args": [
        "compose",
        "up",
        "-d",
        "--build"
      ]
    }
  }
}

OpenAI MCP Example 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 OpenAI MCP Example?

OpenAI MCP Example is a demo application that showcases the Model Context Protocol (MCP) with OpenAI, Azure OpenAI, and GitHub Models. It provides a terminal-based agent that can perform actions using tools exposed by an MCP server, backed by a DocumentDB Local database.

How to use OpenAI MCP Example?

Run the MCP host after starting the MCP server implementations (HTTP and SSE) and configuring an LLM provider via environment variables. Use npm start --prefix mcp-server-http and npm start --prefix mcp-server-sse to start the servers, then npm start --prefix mcp-host to launch the host agent. Alternatively, use docker compose up to run everything in containers.

Key features of OpenAI MCP Example

Supports Azure OpenAI, OpenAI, and GitHub Models as LLM providers.
Provides both HTTP streaming and SSE (Server-Sent Events) MCP transports.
Includes tools: add_todo, list_todos, complete_todo, delete_todo.
Persists state using DocumentDB Local database.
Debugging via DEBUG=mcp:* environment variable.

Use cases of OpenAI MCP Example

Interact with a shopping list agent that can add, list, complete, and delete items.
Test and compare different MCP transport protocols (HTTP vs SSE) with a single host.
Experiment with multiple LLM providers (OpenAI, Azure OpenAI, GitHub Models) in the same demo.

よくある質問

What LLM providers are supported?

Azure OpenAI (Responses API), OpenAI (Responses API), and GitHub Models (ChatCompletion API).

What MCP transport protocols are available?

Two implementations are provided: one using HTTP streaming and one using SSE (Server-Sent Events). Both are supported by the host.

How do I run the demo with Docker?

Clone the repository, then run `docker compose up` to start the MCP servers and DocumentDB Local. Access the MCP host container with `docker exec -it mcp-host bash`.

What tools does the agent have access to?

The agent can use four tools: add_todo, list_todos, complete_todo, and delete_todo.

How can I enable debug logging?

Set the `DEBUG` environment variable to `mcp:*` before starting the MCP host, e.g., `DEBUG=mcp:* npm start --prefix mcp-host`.

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