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The Model Context Protocol (MCP) is an open standard for connecting AI agents to external tools and data sources. Agno provides first-class MCP support. 
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools("npx -y @modelcontextprotocol/server-filesystem .") as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("List all Python files")

asyncio.run(main())

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Capabilities

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Filesystem Server

Access local files and directories through MCP.
cookbook/91_models/mcp/filesystem.py
import asyncio
from pathlib import Path
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mcp import MCPTools

async def run_agent(message: str):
    async with MCPTools(
        f"npx -y @modelcontextprotocol/server-filesystem {Path.cwd()}"
    ) as mcp_tools:
        agent = Agent(
            model=OpenAIChat(id="gpt-4o"),
            tools=[mcp_tools],
            instructions="You are a filesystem assistant.",
            markdown=True,
        )
        await agent.aprint_response(message, stream=True)

asyncio.run(run_agent("What is the license for this project?"))

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Brave Search Server

Web search through the Brave Search MCP server.
cookbook/91_models/mcp/brave.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        "npx -y @anthropic-ai/mcp-server-brave-search",
        env={"BRAVE_API_KEY": "your-key"},
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("Search for recent AI news")

asyncio.run(main())

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Supabase Server

Database operations through Supabase MCP.
cookbook/91_models/mcp/supabase.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        "npx -y @supabase/mcp-server",
        env={
            "SUPABASE_URL": "https://your-project.supabase.co",
            "SUPABASE_KEY": "your-key",
        },
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("List all tables in the database")

asyncio.run(main())

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Qdrant Vector Database

Vector search through Qdrant MCP.
cookbook/91_models/mcp/qdrant.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        "npx -y @qdrant/mcp-server",
        env={"QDRANT_URL": "http://localhost:6333"},
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("Search for documents about machine learning")

asyncio.run(main())

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Multiple MCP Servers

Combine multiple MCP servers in one agent.
cookbook/91_models/mcp/multiple_servers.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools("npx -y @modelcontextprotocol/server-filesystem .") as fs_mcp:
        async with MCPTools("npx -y @anthropic-ai/mcp-server-brave-search") as search_mcp:
            agent = Agent(tools=[fs_mcp, search_mcp])
            await agent.aprint_response(
                "Find Python files in this directory and search for their documentation online"
            )

asyncio.run(main())

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Tool Filtering

Include or exclude specific tools from an MCP server.
cookbook/91_models/mcp/include_tools.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        "npx -y @modelcontextprotocol/server-filesystem .",
        include_tools=["read_file", "list_directory"],
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("What files are here?")

asyncio.run(main())

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Local MCP Server

Build and run your own MCP server.
cookbook/91_models/mcp/local_server/server.py
from mcp.server import Server
from mcp.types import Tool, TextContent

server = Server("my-server")

@server.tool()
async def hello(name: str) -> list[TextContent]:
    """Say hello to someone."""
    return [TextContent(type="text", text=f"Hello, {name}!")]

if __name__ == "__main__":
    import asyncio
    asyncio.run(server.run())
cookbook/91_models/mcp/local_server/client.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools("python server.py") as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("Say hello to the world")

asyncio.run(main())

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SSE Transport

Use Server-Sent Events transport for MCP.
cookbook/91_models/mcp/sse_transport/client.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        transport="sse",
        url="http://localhost:8000/mcp",
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("Use the remote tools")

asyncio.run(main())

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Pipedream Integrations

Connect to 1000+ APIs through Pipedream MCP servers.
cookbook/91_models/mcp/pipedream_slack.py
import asyncio
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def main():
    async with MCPTools(
        "npx -y @anthropic-ai/mcp-server-pipedream",
        env={"PIPEDREAM_API_KEY": "your-key"},
    ) as mcp:
        agent = Agent(tools=[mcp])
        await agent.aprint_response("Send a message to #general on Slack")

asyncio.run(main())

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Run Examples

git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/91_models/mcp

# Filesystem
python filesystem.py

# Multiple servers
python multiple_servers.py

# Custom server
cd local_server && python client.py