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Documentation Index

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Agents use tools to take actions and interact with external systems. Tools are functions that an Agent can run to achieve tasks. For example: searching the web, running SQL, sending an email or calling APIs. You can use any python function as a tool or use a pre-built Agno toolkit. The general syntax is: 
from agno.agent import Agent

agent = Agent(
    # Add functions or Toolkits
    tools=[...],
)

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Using a Toolkit

Agno provides many pre-built toolkits that you can add to your Agents. For example, let’s use the DuckDuckGo toolkit to search the web.
You can find more toolkits in the Toolkits guide.
1

Create Web Search Agent

Create a file web_search.py
web_search.py
from agno.agent import Agent
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(tools=[DuckDuckGoTools()], markdown=True)
agent.print_response("Whats happening in France?", stream=True)
2

Run the agent

Install libraries
pip install openai ddgs agno
Run the agent
python web_search.py

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Writing your own Tools

For more control, write your own python functions and add them as tools to an Agent. For example, here’s how to add a get_top_hackernews_stories tool to an Agent.
hn_agent.py
import json
import httpx

from agno.agent import Agent

def get_top_hackernews_stories(num_stories: int = 10) -> str:
    """Use this function to get top stories from Hacker News.

    Args:
        num_stories (int): Number of stories to return. Defaults to 10.
    """

    # Fetch top story IDs
    response = httpx.get('https://hacker-news.firebaseio.com/v0/topstories.json')
    story_ids = response.json()

    # Fetch story details
    stories = []
    for story_id in story_ids[:num_stories]:
        story_response = httpx.get(f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json')
        story = story_response.json()
        if "text" in story:
            story.pop("text", None)
        stories.append(story)
    return json.dumps(stories)

agent = Agent(tools=[get_top_hackernews_stories], markdown=True)
agent.print_response("Summarize the top 5 stories on hackernews?", stream=True)
Read more about:

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Accessing built-in parameters in tools

You can access agent attributes like session_state, dependencies, agent and team in your tools.
To access session data, like session_state and dependencies, you will use the run_context object. See the RunContext schema for more information.
For example: 
from agno.agent import Agent
from agno.run import RunContext

def get_shopping_list(run_context: RunContext) -> str:
    """Get the shopping list."""
    return run_context.session_state["shopping_list"]

agent = Agent(tools=[get_shopping_list], session_state={"shopping_list": ["milk", "bread", "eggs"]}, markdown=True)
agent.print_response("What's on my shopping list?", stream=True)
See more in the Tool Built-in Parameters section.

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MCP Tools

Agno supports Model Context Protocol (MCP) tools. The general syntax is: 
from agno.agent import Agent
from agno.tools.mcp import MCPTools

async def run_mcp_agent():

    # Initialize the MCP tools
    mcp_tools = MCPTools(command=f"uvx mcp-server-git")

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

    agent = Agent(tools=[mcp_tools], markdown=True)
    await agent.aprint_response("What is the license for this project?", stream=True)
    ...
Learn more about MCP tools in the MCP tools guide.

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Developer Resources