Built-in Tools

pip install yfinance

from agno.agent import Agent
from agno.tools.yfinance import YFinanceTools

agent = Agent(
    tools=[YFinanceTools()],
    instructions="You are a financial analyst.",
    markdown=True
)

agent.print_response("What is the current price of NVDA?")

# Only basic stock information
tools = YFinanceTools(
    enable_stock_price=True,
    enable_company_info=True,
    enable_historical_prices=True,
)

# All financial analysis functions
tools = YFinanceTools(all=True)

# Custom combination
tools = YFinanceTools(
    enable_stock_price=True,
    enable_analyst_recommendations=True,
    enable_company_news=True,
)

from agno.agent import Agent
from agno.tools.yfinance import YFinanceTools

# Create agent with full financial capabilities
agent = Agent(
    tools=[YFinanceTools(all=True)],
    description="You are a comprehensive investment analyst.",
    instructions=[
        "Use any financial function for investment analysis",
        "Format responses using markdown and tables",
        "Provide detailed analysis and insights",
        "Include relevant financial metrics",
    ],
    markdown=True,
)

agent.print_response(
    "Provide a comprehensive analysis of TSLA including price, "
    "fundamentals, and analyst views",
    markdown=True
)

pip install duckduckgo-search

from agno.agent import Agent
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    tools=[DuckDuckGoTools()],
    instructions="Search the web for information."
)

agent.print_response("What are the latest developments in AI?")

from agno.tools.duckduckgo import DuckDuckGoTools

tools = DuckDuckGoTools(
    enable_search=True,      # Enable web search
    enable_news=True,        # Enable news search
    fixed_max_results=5,     # Limit results
    timelimit="w",          # Time limit: d, w, m, y
    region="us-en",         # Region code
    timeout=10,             # Request timeout
)

pip install pygithub

from agno.agent import Agent
from agno.tools.github import GithubTools
import os

agent = Agent(
    tools=[GithubTools(access_token=os.getenv("GITHUB_ACCESS_TOKEN"))],
    instructions="You can interact with GitHub repositories."
)

agent.print_response("Search for Python ML repositories with over 1000 stars")

from agno.agent import Agent
from agno.tools.github import GithubTools
import os

# Create agent with GitHub access
agent = Agent(
    tools=[GithubTools(
        access_token=os.getenv("GITHUB_ACCESS_TOKEN"),
        # Optional: filter available tools
        include_tools=[
            "search_repositories",
            "get_repository",
            "create_issue",
            "get_pull_request",
        ]
    )],
    instructions=[
        "Help users interact with GitHub repositories",
        "Always confirm before creating issues or PRs",
        "Provide clear summaries of repository information",
    ],
    markdown=True,
)

agent.print_response(
    "Find the top 5 Python web frameworks on GitHub and "
    "summarize their features"
)

pip install firecrawl-py

from agno.agent import Agent
from agno.tools.firecrawl import FirecrawlTools
import os

agent = Agent(
    tools=[FirecrawlTools(api_key=os.getenv("FIRECRAWL_API_KEY"))],
    instructions="Extract and summarize web content."
)

agent.print_response("Scrape https://example.com and summarize the content")

pip install psycopg[binary] sqlalchemy

from agno.agent import Agent
from agno.tools.postgres import PostgresTools

# Database connection
db_url = "postgresql+psycopg://user:password@localhost:5432/mydb"

agent = Agent(
    tools=[PostgresTools(db_url=db_url)],
    instructions="You can query the database.",
    markdown=True
)

agent.print_response("Show me the top 10 customers by revenue")

pip install slack-sdk

from agno.agent import Agent
from agno.tools.slack import SlackTools
import os

agent = Agent(
    tools=[SlackTools(token=os.getenv("SLACK_BOT_TOKEN"))],
    instructions="You can send messages to Slack."
)

agent.print_response("Send a summary of today's tasks to #general")

from agno.agent import Agent
from agno.knowledge.pdf import PDFKnowledgeBase
from agno.vectordb.pgvector import PgVector
from agno.tools.knowledge import KnowledgeTools

# Create knowledge base
knowledge = PDFKnowledgeBase(
    path="data/pdfs",
    vector_db=PgVector(
        table_name="pdf_documents",
        db_url="postgresql+psycopg://localhost:5432/ai"
    )
)

# Create agent with knowledge access
agent = Agent(
    knowledge=knowledge,
    tools=[KnowledgeTools(knowledge_base=knowledge)],
    instructions="Use the knowledge base to answer questions.",
    search_knowledge=True,
)

agent.print_response("What does the documentation say about deployment?")

pip install pandas matplotlib

from agno.agent import Agent
from agno.tools.python import PythonTools

agent = Agent(
    tools=[PythonTools()],
    instructions="You can write and execute Python code.",
    markdown=True
)

agent.print_response(
    "Create a bar chart showing monthly sales: "
    "Jan:10000, Feb:12000, Mar:15000, Apr:11000"
)

from agno.agent import Agent
from agno.tools.shell import ShellTools

agent = Agent(
    tools=[ShellTools()],
    instructions="You can run shell commands."
)

agent.print_response("List all Python files in the current directory")

from agno.agent import Agent
from agno.tools.api import APITools

agent = Agent(
    tools=[APITools()],
    instructions="You can make API requests."
)

agent.print_response("Get data from https://api.github.com/users/octocat")