What LLM providers are supported?
Azure OpenAI (Responses API), OpenAI (Responses API), and GitHub Models (ChatCompletion API).
@manekinekko
基本信息
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.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"openai-mcp-example": {
"command": "docker",
"args": [
"compose",
"up",
"-d",
"--build"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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.
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.
DEBUG=mcp:* environment variable.Azure OpenAI (Responses API), OpenAI (Responses API), and GitHub Models (ChatCompletion API).
Two implementations are provided: one using HTTP streaming and one using SSE (Server-Sent Events). Both are supported by the host.
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`.
The agent can use four tools: add_todo, list_todos, complete_todo, and delete_todo.
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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