Anthropic Tool Use: Developer Guide and Quick Start 2026
Learn Anthropic Tool Use: how to use tools/function calling with Claude
Anthropic Tool Use: Developer Guide and Quick Start 2026
Learn Anthropic Tool Use: how to use tools/function calling with Claude
Anthropic Tool Use: Developer Guide 2026 What is Anthropic Tool Use? **Anthropic Tool Use** enables how to use tools/function calling with Claude. This guide covers everything you need to get started quickly. Why Use Anthropic Tool Use? - Solves
Anthropic Tool Use: Developer Guide 2026
What is Anthropic Tool Use?
Anthropic Tool Use enables how to use tools/function calling with Claude. This guide covers everything you need to get started quickly.
Why Use Anthropic Tool Use?
Quick Setup
bash
Install the required package
pip install anthropic-tool-use
or
npm install anthropic-tool-useConfigure credentials
export ANTHROPIC_TOOL_USE_KEY=your_key_here
Basic Usage
python
import osInitialize
client = init_anthropic_tool_use(
api_key=os.environ["ANTHROPIC_TOOL_USE_KEY"]
)Basic operation
result = client.run({
"input": "Your input for how to use tools/function calling with Claude",
"config": {"mode": "production"}
})print(result.output)
Core Concepts
Concept 1: Basic Integration
python
from openai import OpenAI
import osAnthropic Tool Use integrates with your existing AI pipeline
def integrate_anthropic_tool_use(data: dict) -> dict:
"""Integrate Anthropic Tool Use into your workflow."""
# Step 1: Prepare your data
processed = preprocess(data)
# Step 2: Call the service
response = call_service(processed)
# Step 3: Handle the response
return {
"result": response.output,
"metadata": response.metadata,
"status": "success"
}
Concept 2: Advanced Configuration
python
config = {
"model": "latest",
"parameters": {
"quality": "high",
"timeout": 30,
"retry_attempts": 3
},
"output_format": "json",
"callback_url": None # Optional webhook
}Apply configuration
client.configure(config)
Real Example
python
Complete working example for how to use tools/function calling with Claude
import asyncio
import osasync def main():
# Initialize the service
service = Service(api_key=os.environ["API_KEY"])
# Process your request
result = await service.process_async(
input_data="Your actual input for how to use tools/function calling with Claude",
options={"format": "structured"}
)
# Handle the result
if result.success:
print("Output:", result.data)
print("Processed in:", result.latency_ms, "ms")
else:
print("Error:", result.error)
asyncio.run(main())
Production Patterns
python
Production-ready implementation
import logging
from typing import Optional
from functools import lru_cachelogger = logging.getLogger(__name__)
class AnthropicToolUseService:
"""Production service for Anthropic Tool Use."""
def __init__(self, api_key: str):
self._client = None
self._api_key = api_key
@property
def client(self):
if not self._client:
self._client = self._init_client()
return self._client
def _init_client(self):
logger.info(f"Initializing Anthropic Tool Use client")
return create_client(self._api_key)
def process(self, input_data: str) -> Optional[dict]:
try:
result = self.client.run(input_data)
logger.info(f"Successfully processed request")
return result
except Exception as e:
logger.error(f"Error processing: {e}")
return None
Global singleton
_service: Optional[AnthropicToolUseService] = Nonedef get_service() -> AnthropicToolUseService:
global _service
if not _service:
_service = AnthropicToolUseService(os.environ["API_KEY"])
return _service
Pricing and Limits
Troubleshooting
Authentication errors: Check your API key is set correctly in environment variables.
Rate limit errors: Implement exponential backoff (see error handling patterns above).
Timeout errors: Increase timeout or switch to async processing for long-running tasks.
Conclusion
Anthropic Tool Use provides an excellent solution for how to use tools/function calling with Claude. The setup is straightforward and the production patterns shown here will serve you well as you scale.
*Anthropic Tool Use guide | May 2026*
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