Tools

Learn how to use tools in Agno to build AI agents.

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=[...],
)

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
   

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:

• Available toolkits
• Creating your own tools

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.

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.

Developer Resources

• View the Agent schema
• View the Knowledge schema
• View Cookbook