> ## Documentation Index
> Fetch the complete documentation index at: https://ikun.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Streamable HTTP Transport

新的 [Streamable HTTP transport](https://modelcontextprotocol.io/specification/draft/basic/transports#streamable-http) 取代了 2024-11-05 协议版本中的 HTTP+SSE transport。

此传输使 MCP 服务器能够处理多个客户端连接，同时还可以使用 SSE 进行服务器到客户端的流式传输。

要使用它，请初始化 `MCPTools`，传入 MCP 服务器的 URL 并将 transport 设置为 `streamable-http`：

```python theme={null}
from agno.agent import Agent
    from agno.models.openai import OpenAIChat
    from agno.tools.mcp import MCPTools

    server_url = "http://localhost:8000/mcp"

    async with MCPTools(url=server_url, transport="streamable-http") as mcp_tools:
        agent = Agent(model=OpenAIChat(id="gpt-4o"), tools=[mcp_tools])
        await agent.aprint_response("What is the license for this project?", stream=True)
```

您还可以使用 `server_params` 参数来定义 MCP 连接。这样，您可以指定每次请求发送到 MCP 服务器的标头和超时值：

```python theme={null}
from agno.tools.mcp import MCPTools, StreamableHTTPClientParams

server_params = StreamableHTTPClientParams(
    url=...,
    headers=...,
    timeout=...,
    sse_read_timeout=...,
    terminate_on_close=...,

)

async with MCPTools(server_params=server_params) as mcp_tools:
    ...
```

## 完整示例

让我们设置一个简单的本地服务器并使用 Streamable HTTP 传输进行连接：

<Steps>
  <Step title="设置服务器">
    ```python streamable_http_server.py theme={null}
    from mcp.server.fastmcp import FastMCP

    mcp = FastMCP("calendar_assistant")


    @mcp.tool()
    def get_events(day: str) -> str:
        return f"There are no events scheduled for {day}."


    @mcp.tool()
    def get_birthdays_this_week() -> str:
        return "It is your mom's birthday tomorrow"


    if __name__ == "__main__":
        mcp.run(transport="streamable-http")
    ```
  </Step>

  <Step title="设置客户端">
    ```python streamable_http_client.py theme={null}
    import asyncio

    from agno.agent import Agent
    from agno.models.openai import OpenAIChat
    from agno.tools.mcp import MCPTools, MultiMCPTools

    # 这是我们想要使用的 MCP 服务器的 URL。
    server_url = "http://localhost:8000/mcp"


    async def run_agent(message: str) -> None:
        async with MCPTools(transport="streamable-http", url=server_url) as mcp_tools:
            agent = Agent(
                model=OpenAIChat(id="gpt-4o"),
                tools=[mcp_tools],
                markdown=True,
            )
            await agent.aprint_response(message=message, stream=True, markdown=True)


    # 使用 MultiMCPTools，我们可以一次连接到多个 MCP 服务器，即使它们使用不同的传输。
    # 在此示例中，我们连接到我们的示例服务器（Streamable HTTP 传输）和一个不同的服务器（stdio 传输）。
    async def run_agent_with_multimcp(message: str) -> None:
        async with MultiMCPTools(
            commands=["npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt"],
            urls=[server_url],
            urls_transports=["streamable-http"],
        ) as mcp_tools:
            agent = Agent(
                model=OpenAIChat(id="gpt-4o"),
                tools=[mcp_tools],
                markdown=True,
            )
            await agent.aprint_response(message=message, stream=True, markdown=True)


    if __name__ == "__main__":
        asyncio.run(run_agent("Do I have any birthdays this week?"))
        asyncio.run(
            run_agent_with_multimcp(
                "Can you check when is my mom's birthday, and if there are any AirBnb listings in SF for two people for that day?"
            )
        )
    ```
  </Step>

  <Step title="运行服务器">
    ```bash theme={null}
    python streamable_http_server.py
    ```
  </Step>

  <Step title="运行客户端">
    ```bash theme={null}
    python sse_client.py
    ```
  </Step>
</Steps>