Client

Connect an OpenAI agent to an SSE MCP server with MCPTools, and to SSE plus stdio servers together with MultiMCPTools.

Connect to MCP servers that use SSE transport with MCPTools and MultiMCPTools.

client.py

"""
Show how to connect to MCP servers that use the SSE transport using our MCPTools and MultiMCPTools classes.
Check the README.md file for instructions on how to run these examples.
"""

import asyncio

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

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


# This is the URL of the MCP server we want to use.
server_url = "http://localhost:8000/sse"


async def run_agent(message: str) -> None:
    mcp_tools = MCPTools(
        transport="sse",
        url=server_url,
        refresh_connection=True,  # (Optional) Refresh the MCP connection and tools on each run
    )
    await mcp_tools.connect()
    agent = Agent(
        model=OpenAIChat(id="gpt-4o"),
        tools=[mcp_tools],
        markdown=True,
    )
    await agent.aprint_response(input=message, stream=True, markdown=True)
    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 (SSE transport), and a different server (stdio transport).
async def run_agent_with_multimcp(message: str) -> None:
    mcp_tools = MultiMCPTools(
        commands=["npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt"],
        urls=[server_url],
        urls_transports=["sse"],
        refresh_connection=True,  # (Optional) Refresh the MCP connection and tools on each run
    )
    await mcp_tools.connect()
    agent = Agent(
        model=OpenAIChat(id="gpt-4o"),
        tools=[mcp_tools],
        markdown=True,
    )
    await agent.aprint_response(input=message, stream=True, markdown=True)
    await mcp_tools.close()


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    asyncio.run(run_agent("Do I have any birthdays this week?"))
    asyncio.run(run_agent("What else is on my calendar 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?"
        )
    )

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U "agno[mcp]" openai
   
3. Prepare Node.js

   The MCP server runs with npx. Install Node.js, then verify the commands:

   node --version
   npx --version
   
4. Export your OpenAI API key

   Mac/Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   

   $Env:OPENAI_API_KEY="your_openai_api_key_here"
   
5. Clone Agno

   Clone the repository and run the remaining commands from its root:

   git clone https://github.com/agno-agi/agno.git
   cd agno
   
6. Start the SSE server

   In another terminal, start the companion MCP server on port 8000:

   python cookbook/91_tools/mcp/sse_transport/server.py
   
7. Run the example

   Run the example from the repository root:

   python cookbook/91_tools/mcp/sse_transport/client.py
   

Full source: cookbook/91_tools/mcp/sse_transport/client.py