The Model Context Protocol (MCP) enables Agents to interact with external systems through a standardized interface. With Agno’s MCP integration, you can connect any MCP-compatible service to your Agents.

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Example: Filesystem Agent

Here’s a filesystem agent that uses the Filesystem MCP server to explore and analyze files:

filesystem_agent.py
import asyncio
from pathlib import Path
from textwrap import dedent

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


async def run_agent(message: str) -> None:
    """Run the filesystem agent with the given message."""

    file_path = str(Path(__file__).parent.parent.parent.parent)

    # MCP server to access the filesystem (via `npx`)
    async with MCPTools(f"npx -y @modelcontextprotocol/server-filesystem {file_path}") as mcp_tools:
        agent = Agent(
            model=OpenAIChat(id="gpt-4o"),
            tools=[mcp_tools],
            instructions=dedent("""\
                You are a filesystem assistant. Help users explore files and directories.

                - Navigate the filesystem to answer questions
                - Use the list_allowed_directories tool to find directories that you can access
                - Provide clear context about files you examine
                - Use headings to organize your responses
                - Be concise and focus on relevant information\
            """),
            markdown=True,
            show_tool_calls=True,
        )

        # Run the agent
        await agent.aprint_response(message, stream=True)


# Example usage
if __name__ == "__main__":
    # Basic example - exploring project license
    asyncio.run(run_agent("What is the license for this project?"))

​
Multiple MCP Servers

You can use multiple MCP servers in a single agent by using the MultiMCPTools class.

multiple_mcp_servers.py
import asyncio
import os

from agno.agent import Agent
from agno.tools.mcp import MultiMCPTools


async def run_agent(message: str) -> None:
    """Run the Airbnb and Google Maps agent with the given message."""

    env = {
        **os.environ,
        "GOOGLE_MAPS_API_KEY": os.getenv("GOOGLE_MAPS_API_KEY"),
    }

    async with MultiMCPTools(
        [
            "npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt",
            "npx -y @modelcontextprotocol/server-google-maps",
        ],
        env=env,
    ) as mcp_tools:
        agent = Agent(
            tools=[mcp_tools],
            markdown=True,
            show_tool_calls=True,
        )

        await agent.aprint_response(message, stream=True)


# Example usage
if __name__ == "__main__":
    # Pull request example
    asyncio.run(
        run_agent(
            "What listings are available in Cape Town for 2 people for 3 nights from 1 to 4 August 2025?"
        )
    )

​
More Flexibility

You can also create the MCP server yourself and pass it to the MCPTools constructor.

filesystem_agent.py
import asyncio
from pathlib import Path
from textwrap import dedent

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mcp import MCPTools
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client


async def create_filesystem_agent(session):
    """Create and configure a filesystem agent with MCP tools."""
    # Initialize the MCP toolkit
    mcp_tools = MCPTools(session=session)
    await mcp_tools.initialize()

    # Create an agent with the MCP toolkit
    return Agent(
        model=OpenAIChat(id="gpt-4o"),
        tools=[mcp_tools],
        instructions=dedent("""\
            You are a filesystem assistant. Help users explore files and directories.

            - Navigate the filesystem to answer questions
            - Use the list_allowed_directories tool to find directories that you can access
            - Provide clear context about files you examine
            - Use headings to organize your responses
            - Be concise and focus on relevant information\
        """),
        markdown=True,
        show_tool_calls=True,
    )


async def run_agent(message: str) -> None:
    """Run the filesystem agent with the given message."""
    
    # Initialize the MCP server
    server_params = StdioServerParameters(
        command="npx",
        args=[
            "-y",
            "@modelcontextprotocol/server-filesystem",
            str(Path(__file__).parent.parent.parent.parent),  # Set this to the root of the project you want to explore
        ],
    )

    # 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:
            agent = await create_filesystem_agent(session)

            # Run the agent
            await agent.aprint_response(message, stream=True)


# Example usage
if __name__ == "__main__":
    # Basic example - exploring project license
    asyncio.run(run_agent("What is the license for this project?"))

​
Best Practices

  1. Error Handling: Always include proper error handling for MCP server connections and operations.

  2. Resource Cleanup: Use MCPTools or MultiMCPTools as an async context manager to ensure proper cleanup of resources:

async with MCPTools(command) as mcp_tools:
    # Your agent code here
  1. Clear Instructions: Provide clear and specific instructions to your agent:
instructions = """
You are a filesystem assistant. Help users explore files and directories.
- Navigate the filesystem to answer questions
- Use the list_allowed_directories tool to find accessible directories
- Provide clear context about files you examine
- Be concise and focus on relevant information
"""

​
Understanding server Parameters

The recommended way to configure MCPTools or MultiMCPTools is to use the command parameter.

Alternatively, you can use the server_params parameter with MCPTools to configure the connection to the MCP server. It contains the following keys:

  • command: The command to run the MCP server.
    • Use npx for mcp servers that can be installed via npm (or node if running on Windows).
    • Use uvx for mcp servers that can be installed via uvx.
  • args: The arguments to pass to the MCP server.
  • env: Optional environment variables to pass to the MCP server. Remember to include all current environment variables in the env dictionary. If env is not provided, the current environment variables will be used. e.g.
{
    **os.environ,
    "GOOGLE_MAPS_API_KEY": os.getenv("GOOGLE_MAPS_API_KEY"),
}

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More Information

  • Find a collection of MCP servers here.
  • Read the MCP documentation to learn more about the Model Context Protocol.
  • Checkout the Agno Cookbook for more examples of Agents that use MCP.