Adding Tools

def get_weather(location: str) -> str:
    """Get weather for a location."""
    return f"Weather in {location}: 22°C"

agent = Agent(
    name="weather_agent",
    model="openai/gpt-4o-mini",
    tools=[get_weather]  # Function automatically becomes a tool
)

from timbal import Tool

agent = Agent(
    name="weather_agent",
    model="openai/gpt-4o-mini",
    tools=[Tool(handler=get_weather)]
)

Tool(
    handler=get_weather,
    description="Get current weather information for any location"
)

Tool(
    handler=search,
    schema_params_mode="required"  # Only show required params (default: "all")
)

# Include extra parameters even in "required" mode
Tool(
    handler=search_function,
    schema_params_mode="required",
    schema_include_params=["model"]  # Include this optional param
)

# Exclude sensitive or internal parameters
Tool(
    handler=api_function,
    schema_exclude_params=["api_key", "debug_mode"]  # Hide from LLM
)

Tool(
    handler=database_query,
    default_params={
        "timeout": 30
    }
)

def get_current_timestamp():
    return datetime.now().isoformat()

def process_data(data: str, timestamp: str | None = None, user_id: str = "default"):
    return f"Processed {data} at {timestamp} by {user_id}"

# Tool with dynamic default parameters
tool = Tool(
    name="data_processor",
    handler=process_data,
    default_params={
        "timestamp": get_current_timestamp,
        "user_id": "system_user"
    }
)

from timbal import Agent
from timbal.tools import WebSearch

agent = Agent(
    name="research_agent",
    model="openai/gpt-4o-mini",
    tools=[
        WebSearch(
            allowed_domains=["wikipedia.org", "github.com"],  # Restrict to specific domains
            user_location={
                "type": "approximate",
                "country": "US",
                "city": "New York"
            }  # Localize results
        )
    ]
)

general_search = WebSearch()
general_search.name = "general_search"
general_search.description = "Search the web for general information."

domain_search = WebSearch(allowed_domains=["example.com"])
domain_search.name = "domain_search"
domain_search.description = "Search only within example.com domain."

agent = Agent(
    name="research_agent",
    model="anthropic/claude-opus-4-6",
    tools=[general_search, domain_search]
)

from timbal import Agent

def calculate_cost(days: int, hotel_rate: float, flights: float = 0) -> float:
    """Calculate total trip cost."""
    return (days * hotel_rate) + flights

# Pricing specialist agent
pricing_agent = Agent(
    name="pricing_calculator",
    description="Calculate travel costs",  # Tool description for other agents
    model="openai/gpt-4o-mini",
    system_prompt="Answer only with the price. Any text",
    tools=[calculate_cost]
)

# Main travel agent
travel_agent = Agent(
    name="travel_assistant", 
    model="openai/gpt-4o",
    system_prompt="Help plan trips and provide travel advice.",
    tools=[pricing_agent]
)

Tool(handler=get_weather, command="weather")

# User sends: /weather Barcelona
# → runs get_weather(location="Barcelona") directly

from timbal import Agent
from timbal.core import MCPServer

agent = Agent(
    name="my_agent",
    model="openai/gpt-4o-mini",
    tools=[
        MCPServer(
            name="filesystem",
            transport="stdio",
            command="npx",
            args=["-y", "@modelcontextprotocol/server-filesystem", "."],
        ),
    ],
)