Streamable HTTP Transport

The new Streamable HTTP transport replaces the HTTP+SSE transport from protocol version 2024-11-05.

This transport enables the MCP server to handle multiple client connections, and can also use SSE for server-to-client streaming.

To use it, initialize the MCPTools passing the URL of the MCP server and setting the transport to streamable-http:

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.mcp import MCPTools

# Initialize and connect to the Streamable HTTP MCP server
mcp_tools = MCPTools(url="https://docs.agno.com/mcp", transport="streamable-http")
await mcp_tools.connect()

try:
    agent = Agent(model=OpenAIResponses(id="gpt-5.2"), tools=[mcp_tools])
    await agent.aprint_response("What can you tell me about MCP support in Agno?", stream=True)
finally:
    # Always close the connection when done
    await mcp_tools.close()

You can also use the server_params argument to define the MCP connection. This way you can specify the headers to send to the MCP server with every request, and the timeout values:

from agno.tools.mcp import MCPTools, StreamableHTTPClientParams

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

# Initialize and connect using server parameters
mcp_tools = MCPTools(server_params=server_params, transport="streamable-http")
await mcp_tools.connect()

try:
    # Use mcp_tools with your agent
    pass
finally:
    await mcp_tools.close()

Complete example

Let’s set up a simple local server and connect to it using the Streamable HTTP transport:

1. Setup the server

   streamable_http_server.py

   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")
   
2. Setup the client

   streamable_http_client.py

   import asyncio
   
   from agno.agent import Agent
   from agno.models.openai import OpenAIResponses
   from agno.tools.mcp import MCPTools, MultiMCPTools
   
   # This is the URL of the MCP server we want to use.
   server_url = "http://localhost:8000/mcp"
   
   
   async def run_agent(message: str) -> None:
       # Initialize and connect to the Streamable HTTP MCP server
       mcp_tools = MCPTools(transport="streamable-http", url=server_url)
       await mcp_tools.connect()
   
       try:
           agent = Agent(
               model=OpenAIResponses(id="gpt-5.2"),
               tools=[mcp_tools],
               markdown=True,
           )
           await agent.aprint_response(message=message, stream=True, markdown=True)
       finally:
           await mcp_tools.close()
   
   
   # Using MultiMCPTools, we can connect to multiple MCP servers at once, even if they use different transports.
   # In this example we connect to both our example server (Streamable HTTP transport), and a different server (stdio transport).
   async def run_agent_with_multimcp(message: str) -> None:
       # Initialize and connect to multiple MCP servers with different transports
       mcp_tools = MultiMCPTools(
           commands=["npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt"],
           urls=[server_url],
           urls_transports=["streamable-http"],
       )
       await mcp_tools.connect()
   
       try:
           agent = Agent(
               model=OpenAIResponses(id="gpt-5.2"),
               tools=[mcp_tools],
               markdown=True,
           )
           await agent.aprint_response(message=message, stream=True, markdown=True)
       finally:
           await mcp_tools.close()
   
   
   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?"
           )
       )
   
3. Run the server

   python streamable_http_server.py
   
4. Run the client

   python streamable_http_client.py