How to Build AI Agents with Claude API (Step-by-Step)

pip install anthropic

export ANTHROPIC_API_KEY="sk-ant-your-key-here"

$env:ANTHROPIC_API_KEY="sk-ant-your-key-here"

import os
import anthropic

# Quick connection test before building anything else
client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))

response = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=64,
    messages=[{"role": "user", "content": "Say: API connection successful"}]
)

print(response.content[0].text)

import os
import json
import math
import datetime
import anthropic

client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))

# Tool schemas tell Claude what each tool does and what inputs it expects
TOOLS = [
    {
        "name": "get_current_datetime",
        "description": "Returns the current date and time in a human-readable format.",
        "input_schema": {
            "type": "object",
            "properties": {},
            "required": []
        }
    },
    {
        "name": "calculate",
        "description": (
            "Evaluates a mathematical expression and returns the result. "
            "Supports standard arithmetic, powers, and math functions like sqrt, log, sin, cos."
        ),
        "input_schema": {
            "type": "object",
            "properties": {
                "expression": {
                    "type": "string",
                    "description": "A valid Python math expression, e.g. '2 ** 10' or 'math.sqrt(144)'"
                }
            },
            "required": ["expression"]
        }
    },
    {
        "name": "get_weather",
        "description": "Returns current weather conditions for a given city.",
        "input_schema": {
            "type": "object",
            "properties": {
                "city": {
                    "type": "string",
                    "description": "The name of the city, e.g. 'Naples, FL'"
                }
            },
            "required": ["city"]
        }
    }
]


def get_current_datetime() -> str:
    now = datetime.datetime.now()
    return now.strftime("Today is %A, %B %d, %Y. The current time is %I:%M %p.")


def calculate(expression: str) -> str:
    try:
        # Provide math module in eval context so Claude can use math.sqrt() etc.
        result = eval(expression, {"__builtins__": {}}, {"math": math})
        return f"Result: {result}"
    except Exception as e:
        return f"Calculation error: {str(e)}"


def get_weather(city: str) -> str:
    # Mock response — swap this for a real weather API call in production
    mock_data = {
        "naples": "Sunny, 88°F, humidity 72%, light southwest wind.",
        "miami": "Partly cloudy, 85°F, humidity 80%, calm wind.",
        "new york": "Overcast, 74°F, humidity 60%, northeast wind 12 mph.",
    }
    key = city.lower().replace(",", "").split()[0]
    weather = mock_data.get(key, f"Weather data not available for {city}.")
    return f"Weather in {city}: {weather}"


def run_tool(tool_name: str, tool_input: dict) -> str:
    """Dispatch table — maps tool names to their Python functions."""
    if tool_name == "get_current_datetime":
        return get_current_datetime()
    elif tool_name == "calculate":
        return calculate(tool_input["expression"])
    elif tool_name == "get_weather":
        return get_weather(tool_input["city"])
    else:
        return f"Unknown tool: {tool_name}"

class AgentLoop:
    """
    Wraps the Claude API agentic loop.
    Keeps sending messages until Claude produces a final text response.
    """

    def __init__(self, system_prompt: str = None):
        self.client = client
        self.model = "claude-sonnet-4-6"
        self.tools = TOOLS
        self.system_prompt = system_prompt or (
            "You are a helpful AI assistant with access to tools. "
            "Use them whenever they would help you answer accurately. "
            "Always be concise and direct."
        )

    def run(self, user_message: str) -> str:
        """Run the agentic loop for a single user query. Returns the final answer."""

        messages = [{"role": "user", "content": user_message}]
        print(f"\n🤔 User: {user_message}")

        while True:
            response = self.client.messages.create(
                model=self.model,
                max_tokens=1024,
                system=self.system_prompt,
                tools=self.tools,
                messages=messages
            )

            # If Claude is done, extract and return the text response
            if response.stop_reason == "end_turn":
                final_text = ""
                for block in response.content:
                    if hasattr(block, "text"):
                        final_text += block.text
                print(f"\n✅ Agent: {final_text}")
                return final_text

            # Claude wants to call one or more tools
            if response.stop_reason == "tool_use":
                # Add Claude's response (including tool_use blocks) to message history
                messages.append({"role": "assistant", "content": response.content})

                # Collect results for all tool calls in this response
                tool_results = []
                for block in response.content:
                    if block.type == "tool_use":
                        tool_name = block.name
                        tool_input = block.input
                        print(f"\n🔧 Calling tool: {tool_name} | Input: {tool_input}")

                        result = run_tool(tool_name, tool_input)
                        print(f"   ↳ Result: {result}")

                        tool_results.append({
                            "type": "tool_result",
                            "tool_use_id": block.id,
                            "content": result
                        })

                # Send all tool results back to Claude in one user turn
                messages.append({"role": "user", "content": tool_results})

            else:
                # Unexpected stop reason — break to avoid infinite loop
                print(f"Unexpected stop_reason: {response.stop_reason}")
                break

        return "Agent loop ended without a final response."

def main():
    agent = AgentLoop()

    test_queries = [
        "What day of the week is it today, and what time is it?",
        "What is the square root of 1764, and what is 2 to the power of 16?",
        "What's the weather like in Naples, FL right now?"
    ]

    for query in test_queries:
        agent.run(query)
        print("\n" + "─" * 60)


if __name__ == "__main__":
    main()

🤔 User: What day of the week is it today, and what time is it?

🔧 Calling tool: get_current_datetime | Input: {}
   ↳ Result: Today is Wednesday, August 13, 2026. The current time is 10:24 AM.

✅ Agent: Today is Wednesday, August 13, 2026, and the current time is 10:24 AM.

────────────────────────────────────────────────────────────

🤔 User: What is the square root of 1764, and what is 2 to the power of 16?

🔧 Calling tool: calculate | Input: {'expression': 'math.sqrt(1764)'}
   ↳ Result: Result: 42.0

🔧 Calling tool: calculate | Input: {'expression': '2 ** 16'}
   ↳ Result: Result: 65536

✅ Agent: The square root of 1764 is 42, and 2 to the power of 16 is 65,536.

────────────────────────────────────────────────────────────

🤔 User: What's the weather like in Naples, FL right now?

🔧 Calling tool: get_weather | Input: {'city': 'Naples, FL'}
   ↳ Result: Weather in Naples, FL: Sunny, 88°F, humidity 72%, light southwest wind.

✅ Agent: It's currently sunny in Naples, FL with a temperature of 88°F,
humidity at 72%, and a light southwest wind — a classic Southwest Florida day.

anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}}

# The loop keeps printing tool calls but never prints "✅ Agent:"
# No exception is raised — it just runs forever

Calculation error: name 'sqrt' is not defined