client.py
"""
Show how to connect to MCP servers that use either SSE or Streamable HTTP 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/mcp"
async def run_agent(message: str) -> None:
mcp_tools = MCPTools(
transport="streamable-http",
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 (Streamable HTTP 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=["streamable-http"],
refresh_connection=True, # (Optional) Refresh the MCP connection and tools on each run
)
agent = Agent(
model=OpenAIChat(id="gpt-4o"),
tools=[mcp_tools],
markdown=True,
)
await agent.aprint_response(input=message, stream=True, markdown=True)
# ---------------------------------------------------------------------------
# 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
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
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
5
Run the example
Save the code above as
client.py, then run:python client.py