Anthropic Integration¶

Changelog

New in version: 0.7.0

This guide shows how to use ToolRegistry with the Anthropic API (Claude). ToolRegistry generates Anthropic-native tool schemas and reconstructs tool_use / tool_result messages for multi-turn conversations.

Setup ToolRegistry¶

from toolregistry import ToolRegistry

registry = ToolRegistry()

@registry.register
def add(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b

@registry.register
def subtract(a: float, b: float) -> float:
    """Subtract the second number from the first."""
    return a - b

Exposing Tool Schemas¶

schemas = registry.get_schemas(api_format="anthropic")

This returns tools in Anthropic's format:

[
  {
    "name": "add",
    "description": "Add two numbers together.",
    "input_schema": {
      "properties": {
        "a": { "title": "A", "type": "number" },
        "b": { "title": "B", "type": "number" }
      },
      "required": ["a", "b"],
      "title": "addParameters",
      "type": "object"
    }
  },
  {
    "name": "subtract",
    "description": "Subtract the second number from the first.",
    "input_schema": {
      "properties": {
        "a": { "title": "A", "type": "number" },
        "b": { "title": "B", "type": "number" }
      },
      "required": ["a", "b"],
      "title": "subtractParameters",
      "type": "object"
    }
  }
]

Supply Query with Tool Schema¶

import os
import anthropic

client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))

messages = [
    {"role": "user", "content": "I have 15 chestnuts. Joe ate 3. How many do I have left?"}
]

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    tools=schemas,
    messages=messages,
)

Extract Tool Calls¶

Anthropic returns tool use as tool_use content blocks:

tool_calls = [block for block in response.content if block.type == "tool_use"]

Example tool_use block:

{
  "type": "tool_use",
  "id": "toolu_01A09q90qw90lq917835lq9",
  "name": "subtract",
  "input": {"a": 15, "b": 3}
}

Execute Tool Calls¶

ToolRegistry handles Anthropic tool_use blocks natively:

tool_responses = registry.execute_tool_calls(tool_calls)

Returns a dict mapping tool call IDs to results:

{"toolu_01A09q90qw90lq917835lq9": "12"}

Feed Results Back to LLM¶

Reconstruct the conversation messages in Anthropic format:

assistant_tool_messages = registry.build_tool_call_messages(
    tool_calls, tool_responses, api_format="anthropic"
)

This produces Anthropic-native message structure:

[
  {
    "role": "assistant",
    "content": [
      {
        "type": "tool_use",
        "id": "toolu_01A09q90qw90lq917835lq9",
        "name": "subtract",
        "input": {"a": 15, "b": 3}
      }
    ]
  },
  {
    "role": "user",
    "content": [
      {
        "type": "tool_result",
        "tool_use_id": "toolu_01A09q90qw90lq917835lq9",
        "content": "12"
      }
    ]
  }
]

Extend the conversation and get the final answer:

messages.extend(assistant_tool_messages)

second_response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=messages,
)

print(second_response.content[0].text)

Complete Python Script¶

import json
import os

import anthropic
from toolregistry import ToolRegistry

registry = ToolRegistry()

@registry.register
def add(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b

@registry.register
def subtract(a: float, b: float) -> float:
    """Subtract the second number from the first."""
    return a - b

client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))

messages = [
    {"role": "user", "content": "I have 15 chestnuts. Joe ate 3. How many do I have left?"}
]

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    tools=registry.get_schemas(api_format="anthropic"),
    messages=messages,
)

tool_calls = [block for block in response.content if block.type == "tool_use"]

if tool_calls:
    tool_responses = registry.execute_tool_calls(tool_calls)
    print(tool_responses)

    assistant_tool_messages = registry.build_tool_call_messages(
        tool_calls, tool_responses, api_format="anthropic"
    )
    print(json.dumps(assistant_tool_messages, indent=2))

    messages.extend(assistant_tool_messages)
    second_response = client.messages.create(
        model="claude-sonnet-4-20250514",
        max_tokens=1024,
        messages=messages,
    )

    print(second_response.content[0].text)