Example: Adding a Calculator to Our Agent › Step 3: Build the Agent with Tool Support (Claude Sonnet 4.5)

import os
from anthropic import Anthropic

## Using Claude Sonnet 4.5 for its excellent tool use and agent reasoning
client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))

def run_agent_with_calculator(user_message: str) -> str:
    """
    Run the agent with calculator tool support.
    
    Args:
        user_message: The user's question or request
    
    Returns:
        The agent's response
    """
    # Tool registry maps tool names to functions
    tool_registry = {
        "calculate": calculate
    }
    
    # Start the conversation
    messages = [{"role": "user", "content": user_message}]
    
    # Initial agent call with tool description
    response = client.messages.create(
        model="claude-sonnet-4-5",
        max_tokens=1024,
        tools=[calculator_tool],
        messages=messages
    )
    
    # Check if the agent wants to use a tool
    if response.stop_reason == "tool_use":
        # Extract tool use information
        tool_use_block = next(
            block for block in response.content 
            if block.type == "tool_use"
        )
        
        tool_name = tool_use_block.name
        tool_input = tool_use_block.input
        
        print(f"Agent is using tool: {tool_name}")
        print(f"Tool input: {tool_input}")
        
        # Call the tool
        tool_result = tool_registry[tool_name](**tool_input)
        print(f"Tool result: {tool_result}")
        
        # Send the tool result back to the agent
        messages.append({"role": "assistant", "content": response.content})
        messages.append({
            "role": "user",
            "content": [{
                "type": "tool_result",
                "tool_use_id": tool_use_block.id,
                "content": str(tool_result)
            }]
        })
        
        # Get the agent's final response
        final_response = client.messages.create(
            model="claude-sonnet-4-5",
            max_tokens=1024,
            tools=[calculator_tool],
            messages=messages
        )
        
        return final_response.content[0].text
    
    # No tool needed, return direct response
    return response.content[0].text