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layout default
title Chapter 4: Tools, MCP, and Confirmation Flows
nav_order 4
parent ADK Python Tutorial

Chapter 4: Tools, MCP, and Confirmation Flows

Welcome to Chapter 4: Tools, MCP, and Confirmation Flows. In this part of ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.

This chapter explains how to safely expose external capabilities to ADK agents.

Learning Goals

  • use Python tools and OpenAPI/MCP integrations
  • gate risky tool actions with confirmation flows
  • build safer human-in-the-loop controls
  • reduce runtime surprises from tool misuse

Tooling Categories in ADK

  • Python function tools
  • OpenAPI-based tools
  • MCP-based tools
  • Google ecosystem connectors

Confirmation Strategy

For tools with side effects, add explicit confirmation requirements before execution. This keeps the agent useful while reducing accidental writes or external operations.

Source References

Summary

You now have a practical pattern for shipping tool-enabled ADK agents with stronger safety defaults.

Next: Chapter 5: Sessions, Memory, and Context Management

Depth Expansion Playbook

Source Code Walkthrough

contributing/samples/interactions_api/main.py

The test_google_search_tool function in contributing/samples/interactions_api/main.py handles a key part of this chapter's functionality:

async def test_google_search_tool(runner: Runner, session_id: str):
  """Test the google_search built-in tool."""
  print("\n" + "=" * 60)
  print("TEST 4: Google Search Tool (Additional)")
  print("=" * 60)

  response, interaction_id = await call_agent_async(
      runner,
      USER_ID,
      session_id,
      "Use google search to find out who wrote the novel '1984'.",
  )

  assert response, "Expected a non-empty response"
  assert (
      "orwell" in response.lower() or "george" in response.lower()
  ), f"Expected George Orwell in response: {response}"
  print("PASSED: Google search built-in tool works")


async def test_custom_function_tool(runner: Runner, session_id: str):
  """Test the custom function tool alongside google_search.

  The root_agent has both GoogleSearchTool (with bypass_multi_tools_limit=True)
  and get_current_weather. This tests that function calling tools work with
  the Interactions API when all tools are function calling types.
  """
  print("\n" + "=" * 60)
  print("TEST 5: Custom Function Tool (get_current_weather)")
  print("=" * 60)

This function is important because it defines how ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK implements the patterns covered in this chapter.

contributing/samples/interactions_api/main.py

The test_custom_function_tool function in contributing/samples/interactions_api/main.py handles a key part of this chapter's functionality:

async def test_custom_function_tool(runner: Runner, session_id: str):
  """Test the custom function tool alongside google_search.

  The root_agent has both GoogleSearchTool (with bypass_multi_tools_limit=True)
  and get_current_weather. This tests that function calling tools work with
  the Interactions API when all tools are function calling types.
  """
  print("\n" + "=" * 60)
  print("TEST 5: Custom Function Tool (get_current_weather)")
  print("=" * 60)

  response, interaction_id = await call_agent_async(
      runner,
      USER_ID,
      session_id,
      "What's the weather like in Tokyo?",
  )

  assert response, "Expected a non-empty response"
  # The mock weather data for Tokyo has temperature 68, condition "Partly Cloudy"
  assert (
      "68" in response
      or "partly" in response.lower()
      or "tokyo" in response.lower()
  ), f"Expected weather info for Tokyo in response: {response}"
  print("PASSED: Custom function tool works with bypass_multi_tools_limit")
  return interaction_id


def check_interactions_api_available() -> bool:

This function is important because it defines how ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK implements the patterns covered in this chapter.

contributing/samples/interactions_api/main.py

The check_interactions_api_available function in contributing/samples/interactions_api/main.py handles a key part of this chapter's functionality:

def check_interactions_api_available() -> bool:
  """Check if the interactions API is available in the SDK."""
  try:
    from google.genai import Client

    client = Client()
    # Check if interactions attribute exists
    return hasattr(client.aio, "interactions")
  except Exception:
    return False


async def run_all_tests():
  """Run all tests with the Interactions API."""
  print("\n" + "#" * 70)
  print("# Running tests with Interactions API")
  print("#" * 70)

  # Check if interactions API is available
  if not check_interactions_api_available():
    print("\nERROR: Interactions API is not available in the current SDK.")
    print("The interactions API requires a SDK version with this feature.")
    print("To use the interactions API, ensure you have the SDK with")
    print("interactions support installed (e.g., from private-python-genai).")
    return False

  test_agent = root_agent

  runner = InMemoryRunner(
      agent=test_agent,

This function is important because it defines how ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK implements the patterns covered in this chapter.

contributing/samples/interactions_api/main.py

The run_all_tests function in contributing/samples/interactions_api/main.py handles a key part of this chapter's functionality:

async def run_all_tests():
  """Run all tests with the Interactions API."""
  print("\n" + "#" * 70)
  print("# Running tests with Interactions API")
  print("#" * 70)

  # Check if interactions API is available
  if not check_interactions_api_available():
    print("\nERROR: Interactions API is not available in the current SDK.")
    print("The interactions API requires a SDK version with this feature.")
    print("To use the interactions API, ensure you have the SDK with")
    print("interactions support installed (e.g., from private-python-genai).")
    return False

  test_agent = root_agent

  runner = InMemoryRunner(
      agent=test_agent,
      app_name=APP_NAME,
  )

  # Create a new session
  session = await runner.session_service.create_session(
      user_id=USER_ID,
      app_name=APP_NAME,
  )
  print(f"\nSession created: {session.id}")

  try:
    # Run all tests

This function is important because it defines how ADK Python Tutorial: Production-Grade Agent Engineering with Google's ADK implements the patterns covered in this chapter.

How These Components Connect

flowchart TD
    A[test_google_search_tool]
    B[test_custom_function_tool]
    C[check_interactions_api_available]
    D[run_all_tests]
    E[interactive_mode]
    A --> B
    B --> C
    C --> D
    D --> E
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