Model Context Protocol (MCP)

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

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

    # Initialize the MCP tools
    mcp_tools = MCPTools(f"npx -y @modelcontextprotocol/server-filesystem {file_path}")

    # Connect to the MCP server
    await mcp_tools.connect()

    # Use the MCP tools with an Agent
    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)

    # Close the MCP connection
    await mcp_tools.close()


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

from contextlib import asynccontextmanager
from os import getenv
from textwrap import dedent

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.playground import Playground
from agno.storage.agent.sqlite import SqliteAgentStorage
from agno.tools.mcp import MCPTools
from fastapi import FastAPI
from mcp import StdioServerParameters

agent_storage_file: str = "tmp/agents.db"


# MCP server parameters setup
github_token = getenv("GITHUB_TOKEN") or getenv("GITHUB_ACCESS_TOKEN")
if not github_token:
    raise ValueError("GITHUB_TOKEN environment variable is required")

server_params = StdioServerParameters(
    command="npx",
    args=["-y", "@modelcontextprotocol/server-github"],
)


# This is required to start the MCP connection correctly in the FastAPI lifecycle
@asynccontextmanager
async def lifespan(app: FastAPI):
    """Manage MCP connection lifecycle inside a FastAPI app"""
    global mcp_tools

    # Startuplogic: connect to our MCP server
    mcp_tools = MCPTools(server_params=server_params)
    await mcp_tools.connect()

    # Add the MCP tools to our Agent
    agent.tools = [mcp_tools]

    yield

    # Shutdown: Close MCP connection
    await mcp_tools.close()


agent = Agent(
    name="MCP GitHub Agent",
    instructions=dedent("""\
        You are a GitHub assistant. Help users explore repositories and their activity.

        - Use headings to organize your responses
        - Be concise and focus on relevant information\
    """),
    model=OpenAIChat(id="gpt-4o"),
    storage=SqliteAgentStorage(
        table_name="basic_agent",
        db_file=agent_storage_file,
        auto_upgrade_schema=True,
    ),
    add_history_to_messages=True,
    num_history_responses=3,
    add_datetime_to_instructions=True,
    markdown=True,
)

# Setup the Playground app
playground = Playground(
    agents=[agent],
    name="MCP Demo",
    description="A playground for MCP",
    app_id="mcp-demo",
)

# Initialize the Playground app with our lifespan logic
app = playground.get_app(lifespan=lifespan)


if __name__ == "__main__":
    playground.serve(app="mcp_demo:app", reload=True)