mcp_tools.py
"""
Mcp Tools
=============================
Demonstrates mcp tools.
"""
import asyncio
import sys
from pathlib import Path
from agno.agent import Agent
from agno.tools.mcp import MCPTools
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
async def main(prompt: str) -> None:
# Initialize the MCP server
server_params = StdioServerParameters(
command="npx",
args=[
"-y",
"@modelcontextprotocol/server-filesystem",
str(Path(__file__).parent.parent),
],
)
# Create a client session to connect to the MCP server
async with stdio_client(server_params) as (read, write):
async with ClientSession(read, write) as session:
# Initialize the MCP toolkit
mcp_tools = MCPTools(session=session)
await mcp_tools.initialize()
# Create an agent with the MCP toolkit
agent = Agent(tools=[mcp_tools])
# Run the agent
await agent.aprint_response(prompt, stream=True)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
prompt = (
sys.argv[1] if len(sys.argv) > 1 else "Read and summarize the file ./LICENSE"
)
asyncio.run(main(prompt))
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
Clone Agno and run the example from the repository root:
git clone https://github.com/agno-agi/agno.git
cd agno
python cookbook/91_tools/mcp_tools.py