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FastAPI SSE MCP 随机

一个 FastAPI 服务器,它使用服务器发送事件 (SSE) 实现模型上下文协议 (MCP),用于流式通信。该项目提供各种实用工具,包括随机数生成、使用 Azure OpenAI DALL-E 生成图像以及 AI 播客生成。

特征

  • 用于实时流通信的服务器发送事件(SSE)

  • 用于结构化工具使用的**模型上下文协议 (MCP)**实现

  • 多种实用工具

    • Echo 工具和资源

    • 随机数生成器

    • 通过 Azure OpenAI DALL-E 3 生成图像

    • AI播客生成

    • 用于反思性回应的“思考工具”

Related MCP server: AI Agent MCP Server

先决条件

  • Python 3.10+

  • Azure OpenAI API 访问(用于图像生成)

安装

  1. 克隆存储库:

git clone <repository-url>
cd fastapi_sse_mcp_random
  1. 安装依赖项:

pip install -r requirements.txt

或者使用uv

uv pip install -e .

用法

启动服务器

使用以下命令运行服务器:

python main.py

服务器将从http://0.0.0.0:8000启动

可用端点

  • GET / :健康检查端点

  • GET /sse/ :SSE 连接端点

  • POST /messages/ :客户端消息的端点

可用工具

回声工具

{
  "name": "echo_tool",
  "parameters": {
    "message": "Hello, world!"
  }
}

随机数生成器

{
  "name": "random_number",
  "parameters": {
    "min_value": 1,
    "max_value": 100
  }
}

图像生成

{
  "name": "generate_image",
  "parameters": {
    "prompt": "A beautiful landscape with mountains and a lake"
  }
}

播客一代

{
  "name": "generate_podcast",
  "parameters": {
    "prompt": "The future of artificial intelligence",
    "duration": 5,
    "name1": "Mark",
    "voice1": "Thomas",
    "name2": "Sophia",
    "voice2": "Emily"
  }
}

思考工具

{
  "name": "think_tool",
  "parameters": {
    "input": "What are the implications of quantum computing?"
  }
}

项目结构

  • main.py :主要的 FastAPI 应用程序和 MCP 工具实现

  • sse.py :服务器发送事件(SSE)实现

  • pyproject.toml :项目元数据和依赖项

  • requirements.txt :基本依赖项列表

依赖项

  • FastAPI:用于构建 API 的 Web 框架

  • MCP:模型上下文协议实现

  • OpenAI:Azure OpenAI 服务的客户端

  • Uvicorn:用于运行 FastAPI 应用程序的 ASGI 服务器

  • 请求:用于 API 调用的 HTTP 库

执照

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