# Authenticating with Tools

<div class="language-support-tag">
  <span class="lst-supported">Supported in ADK</span><span class="lst-python">Python v0.1.0</span>
</div>

The tools and services you use within ADK agents may require access to protected
resources, such as user data in email or calendar applications, or sales records
in databases. Getting access to these resources typically requires an
authentication process that includes credentials and access keys which must
be carefully managed and protected. The requirements for managing authentication
data can also change if you are running your agent locally or deploying it
to a hosted service. If multiple users, with potentially different access
permissions, are interacting with the agent, this creates another layer of
authentication management requirements.

!!! danger "WARNING: Credential storage and security risks"

    Storing sensitive credentials such as access tokens and especially refresh
    tokens directly in the session state can pose security risks depending on
    your session storage backend, your ***SessionService*** implementation,
    and overall application security posture. Carefully consider how you manage
    credentials in ADK agents before deploying them for general use.

## Authentication and credential management

There are several ways to manage authentication and credentials in ADK
agents. Each of these methods carries some amount of risk, so you should
carefully consider which approach best serves your application and customers.

### Recommended: Authentication manager services {#authentication-manager}

When deploying agents to production hosted environments, your agent's ability to
properly authenticate to restricted tools and services becomes more challenging
and more important to properly manage. This authentication challenge can become
even more complicated when users of your agent have varying levels of access to
restricted tools and data.

Rather than writing code to handle the authentication process and credential
management for various tools used by your agent, use an *authentication manager*
service that manages *both* for you. This service should handle the storage of
keys and secrets, as well as the acquisition, management, and storage of OAuth
access or refresh tokens. Learn more about 
[Agent Identity integration](/integrations/agent-identity/) with ADK.

### Self-managed authentication

If you decide to manage your own authentication process with ADK helper functions
and your own code, consider these recommendations:

*   **API keys and client secrets:** For any API keys and client secrets used
    inside ADK code, when running on a local compute environment use a local
    `.env` file excluded from version control. When your agent is hosted or
    otherwise in a production environment, use a secrets manager. For more
    details on secrets managers, see the [next section](#secrets-manager).
*   **Interactive authentication:** When using interactive three-legged auth
    (3LO) OAuth or OpenID Connect (OIDC) for authentication to tools, write a
    service on the client application to acquire, manage access, and refresh
    tokens. Make sure to store these tokens against an authenticated user
    identifier in an encrypted database.

### Secrets manager services {#secrets-manager}

For production environments, if you are not using an
[authentication manager](#authentication-manager) service, you should store
credentials in a dedicated secret manager service to protect that data. With
this approach, a secret manager securely stores the credentials for any tools or
services accessed by the agent as needed, and those secrets are not resident in
agent's operating memory. For example, a custom ADK Tool using this method would
have only short-lived access tokens or secure references in session memory, and
retrieve longer-lived refresh tokens from the secrets manager when needed. When
selecting a secrets manager, consider services from well-established providers,
such as
[Google Cloud Secret Manager](https://cloud.google.com/security/products/secret-manager)
or other secret management services.

### Local encrypted secrets storage

For agent applications that are less security sensitive, keeping credentials in
local, encrypted storage can be a viable option. Consider using dedicated local
secrets storage system or encrypting the data in a local database using a robust
encryption library, and then managing the encryption keys securely using a key
management service. Take care to only keep short-lived access tokens in
operating memory and access long-lived credentials and refresh tokens from
encrypted local storage only when needed.

### In-memory secrets

This method *should only be used in the early development* and testing of your
agent. With this approach, credentials are stored in the current
***InMemorySessionService*** instance. The data exists only in session memory
and is not persisted. However, you should carefully consider the risks of using
this method based on how long an agent session may last, who has access to the
agent, and the security of the environment where the agent is running.

## Framework components

Within the ADK framework, the ***AuthScheme*** and ***AuthCredential*** are the
key components for handling authentication methods and managing credential data:

*   ***AuthScheme***: Defines *how* an API expects authentication credentials,
    such as an API Key in a header or an OAuth 2.0 Bearer token. ADK supports
    the same types of authentication schemes as OpenAPI 3.0 and uses specific
    classes for credential types, including ***APIKey***, ***HTTPBearer***,
    ***OAuth2***, and ***OpenIdConnectWithConfig***. For more details on each
    OpenAPI credential type, see
    [OpenAPI doc: Authentication](https://swagger.io/docs/specification/v3_0/authentication/).

*   ***AuthCredential***: Holds the *initial* information needed to *start* the
    authentication process, such as your application's OAuth Client ID or
    Secret, or an API key value. An instance of this class includes an
    **auth_type**, such as `API_KEY`, `OAUTH2`, `SERVICE_ACCOUNT`, specifying
    the credential type.

The general authentication flow involves providing these details when
configuring a tool. ADK then attempts to automatically exchange the initial
credential, such as an access token, before the tool makes an API call. For
flows requiring user interaction, including OAuth consent, ADK triggers a
specific interactive process with your ***Agent Client*** application.

### Supported initial credential types

*   **API\_KEY:** Provides simple key-value authentication, which usually
    requires no authentication exchange.
*   **HTTP:** Provides Basic Auth which is not recommended and may not be
    supported for exchange, or already obtained Bearer tokens. Bearer tokens do
    not require an authentication exchange.
*   **OAUTH2:** Provides standard OAuth 2.0 authentication flows, and requires
    configuration with client ID, secret, and scopes. This method often
    triggers an interactive flow for user consent.
*   **OPEN\_ID\_CONNECT:** Provides authentication based on OpenID Connect.
    Similar to OAuth2, this type often requires configuration and user
    interaction.
*   **SERVICE\_ACCOUNT:** Provides Google Cloud Service Account credentials as a
    JSON key or Application Default Credentials. This type typically exchanges a
    Bearer token.

## Tools and integrations quick guide

Here is a quick guide to authentication for key ADK toolsets:

*   [***RestApiTool***](/tools-custom/openapi-tools/):
    Set `auth_scheme` and `auth_credential` during initialization
*   [***OpenAPIToolset***](/tools-custom/openapi-tools/):
    Set `auth_scheme` and `auth_credential` during initialization
*   [***APIHubToolset***](/integrations/apigee-api-hub/):
    Set `auth_scheme` and `auth_credential` during initialization, *if* the API
    requires authentication.
*   [***ApplicationIntegrationToolset***](/integrations/application-integration/):
    Set `auth_scheme` and `auth_credential` during initialization, *if* the API
    requires authentication.
*   [***GoogleApiToolSet***](https://github.com/google/adk-python/blob/main/src/google/adk/tools/google_api_tool/google_api_toolset.py):
    Use this toolset's specific authentication method.

For more authentication details for other pre-built tools and integrations
see the [ADK Integrations](/integrations) catalog.

---

## Journey 1: Building Agentic Applications with Authenticated Tools

This section focuses on using pre-existing tools (like those from `RestApiTool/ OpenAPIToolset`, `APIHubToolset`, `GoogleApiToolSet`) that require authentication within your agentic application. Your main responsibility is configuring the tools and handling the client-side part of interactive authentication flows (if required by the tool).

### 1. Configuring Tools with Authentication

When adding an authenticated tool to your agent, you need to provide its required `AuthScheme` and your application's initial `AuthCredential`.

**A. Using OpenAPI-based Toolsets (`OpenAPIToolset`, `APIHubToolset`, etc.)**

Pass the scheme and credential during toolset initialization. The toolset applies them to all generated tools. Here are few ways to create tools with authentication in ADK.

=== "API Key"

      Create a tool requiring an API Key.

      ```py
      from google.adk.tools.openapi_tool.auth.auth_helpers import token_to_scheme_credential
      from google.adk.tools.openapi_tool.openapi_spec_parser.openapi_toolset import OpenAPIToolset

      auth_scheme, auth_credential = token_to_scheme_credential(
          "apikey", "query", "apikey", "YOUR_API_KEY_STRING"
      )
      sample_api_toolset = OpenAPIToolset(
          spec_str="...",  # Fill this with an OpenAPI spec string
          spec_str_type="yaml",
          auth_scheme=auth_scheme,
          auth_credential=auth_credential,
      )
      ```

=== "OAuth2"

      Create a tool requiring OAuth2.

      ```py
      from google.adk.tools.openapi_tool.openapi_spec_parser.openapi_toolset import OpenAPIToolset
      from fastapi.openapi.models import OAuth2
      from fastapi.openapi.models import OAuthFlowAuthorizationCode
      from fastapi.openapi.models import OAuthFlows
      from google.adk.auth import AuthCredential
      from google.adk.auth import AuthCredentialTypes
      from google.adk.auth import OAuth2Auth

      auth_scheme = OAuth2(
          flows=OAuthFlows(
              authorizationCode=OAuthFlowAuthorizationCode(
                  authorizationUrl="https://accounts.google.com/o/oauth2/auth",
                  tokenUrl="https://oauth2.googleapis.com/token",
                  scopes={
                      "https://www.googleapis.com/auth/calendar": "calendar scope"
                  },
              )
          )
      )
      auth_credential = AuthCredential(
          auth_type=AuthCredentialTypes.OAUTH2,
          oauth2=OAuth2Auth(
              client_id=YOUR_OAUTH_CLIENT_ID,
              client_secret=YOUR_OAUTH_CLIENT_SECRET
          ),
      )

      calendar_api_toolset = OpenAPIToolset(
          spec_str=google_calendar_openapi_spec_str, # Fill this with an openapi spec
          spec_str_type='yaml',
          auth_scheme=auth_scheme,
          auth_credential=auth_credential,
      )
      ```

=== "Service Account"

      Create a tool requiring Service Account.

      ```py
      from google.adk.tools.openapi_tool.auth.auth_helpers import service_account_dict_to_scheme_credential
      from google.adk.tools.openapi_tool.openapi_spec_parser.openapi_toolset import OpenAPIToolset

      service_account_cred = json.loads(service_account_json_str)
      auth_scheme, auth_credential = service_account_dict_to_scheme_credential(
          config=service_account_cred,
          scopes=["https://www.googleapis.com/auth/cloud-platform"],
      )
      sample_toolset = OpenAPIToolset(
          spec_str=sa_openapi_spec_str, # Fill this with an openapi spec
          spec_str_type='json',
          auth_scheme=auth_scheme,
          auth_credential=auth_credential,
      )
      ```

=== "OpenID connect"

      Create a tool requiring OpenID connect.

      ```py
      from google.adk.auth.auth_schemes import OpenIdConnectWithConfig
      from google.adk.auth.auth_credential import AuthCredential, AuthCredentialTypes, OAuth2Auth
      from google.adk.tools.openapi_tool.openapi_spec_parser.openapi_toolset import OpenAPIToolset

      auth_scheme = OpenIdConnectWithConfig(
          authorization_endpoint=OAUTH2_AUTH_ENDPOINT_URL,
          token_endpoint=OAUTH2_TOKEN_ENDPOINT_URL,
          scopes=['openid', 'YOUR_OAUTH_SCOPES"]
      )
      auth_credential = AuthCredential(
          auth_type=AuthCredentialTypes.OPEN_ID_CONNECT,
          oauth2=OAuth2Auth(
              client_id="...",
              client_secret="...",
          )
      )

      userinfo_toolset = OpenAPIToolset(
          spec_str=content, # Fill in an actual spec
          spec_str_type='yaml',
          auth_scheme=auth_scheme,
          auth_credential=auth_credential,
      )
      ```

**B. Using Google API Toolsets (e.g., `calendar_tool_set`)**

These toolsets often have dedicated configuration methods.

Tip: For how to create a Google OAuth Client ID & Secret, see this guide: [Get your Google API Client ID](https://developers.google.com/identity/gsi/web/guides/get-google-api-clientid#get_your_google_api_client_id)

```py
# Example: Configuring Google Calendar Tools
from google.adk.tools.google_api_tool import calendar_tool_set

client_id = "YOUR_GOOGLE_OAUTH_CLIENT_ID.apps.googleusercontent.com"
client_secret = "YOUR_GOOGLE_OAUTH_CLIENT_SECRET"

# Use the specific configure method for this toolset type
calendar_tool_set.configure_auth(
    client_id=oauth_client_id, client_secret=oauth_client_secret
)

# agent = LlmAgent(..., tools=calendar_tool_set.get_tool('calendar_tool_set'))
```

The sequence diagram of auth request flow (where tools are requesting auth credentials) looks like below:

![Authentication](../assets/auth_part1.svg)


### 2. Handling the Interactive OAuth/OIDC Flow (Client-Side)

If a tool requires user login/consent (typically OAuth 2.0 or OIDC), the ADK framework pauses execution and signals your ***Agent Client*** application. There are two cases:

* ***Agent Client*** application runs the agent directly (via `runner.run_async`) in the same process. e.g. UI backend, CLI app, or Spark job etc.
* ***Agent Client*** application interacts with ADK's fastapi server via `/run` or `/run_sse` endpoint. While ADK's fastapi server could be setup on the same server or different server as ***Agent Client*** application

The second case is a special case of first case, because `/run` or `/run_sse` endpoint also invokes `runner.run_async`. The only differences are:

* Whether to call a python function to run the agent (first case) or call a service endpoint to run the agent (second case).
* Whether the result events are in-memory objects (first case) or serialized json string in http response (second case).

Below sections focus on the first case and you should be able to map it to the second case very straightforward. We will also describe some differences to handle for the second case if necessary.

Here's the step-by-step process for your client application:

**Step 1: Run Agent & Detect Auth Request**

* Initiate the agent interaction using `runner.run_async`.
* Iterate through the yielded events.
* Look for a specific function call event whose function call has a special name: `adk_request_credential`. This event signals that user interaction is needed. You can use helper functions to identify this event and extract necessary information. (For the second case, the logic is similar. You deserialize the event from the http response).

```py

# runner = Runner(...)
# session = await session_service.create_session(...)
# content = types.Content(...) # User's initial query

print("\nRunning agent...")
events_async = runner.run_async(
    session_id=session.id, user_id='user', new_message=content
)

auth_request_function_call_id, auth_config = None, None

async for event in events_async:
    # Use helper to check for the specific auth request event
    if (auth_request_function_call := get_auth_request_function_call(event)):
        print("--> Authentication required by agent.")
        # Store the ID needed to respond later
        if not (auth_request_function_call_id := auth_request_function_call.id):
            raise ValueError(f'Cannot get function call id from function call: {auth_request_function_call}')
        # Get the AuthConfig containing the auth_uri etc.
        auth_config = get_auth_config(auth_request_function_call)
        break # Stop processing events for now, need user interaction

if not auth_request_function_call_id:
    print("\nAuth not required or agent finished.")
    # return # Or handle final response if received

```

*Helper functions `helpers.py`:*

```py
from google.adk.events import Event
from google.adk.auth import AuthConfig # Import necessary type
from google.genai import types

def get_auth_request_function_call(event: Event) -> types.FunctionCall:
    # Get the special auth request function call from the event
    if not event.content or not event.content.parts:
        return
    for part in event.content.parts:
        if (
            part
            and part.function_call
            and part.function_call.name == 'adk_request_credential'
            and event.long_running_tool_ids
            and part.function_call.id in event.long_running_tool_ids
        ):

            return part.function_call

def get_auth_config(auth_request_function_call: types.FunctionCall) -> AuthConfig:
    # Extracts the AuthConfig object from the arguments of the auth request function call
    if not auth_request_function_call.args or not (auth_config := auth_request_function_call.args.get('authConfig')):
        raise ValueError(f'Cannot get auth config from function call: {auth_request_function_call}')
    if isinstance(auth_config, dict):
        auth_config = AuthConfig.model_validate(auth_config)
    elif not isinstance(auth_config, AuthConfig):
        raise ValueError(f'Cannot get auth config {auth_config} is not an instance of AuthConfig.')
    return auth_config
```

**Step 2: Redirect User for Authorization**

* Get the authorization URL (`auth_uri`) from the `auth_config` extracted in the previous step.
* **Crucially, append your application's**  redirect\_uri as a query parameter to this `auth_uri`. This `redirect_uri` must be pre-registered with your OAuth provider (e.g., [Google Cloud Console](https://developers.google.com/identity/protocols/oauth2/web-server#creatingcred), [Okta admin panel](https://developer.okta.com/docs/guides/sign-into-web-app-redirect/spring-boot/main/#create-an-app-integration-in-the-admin-console)).
* Direct the user to this complete URL (e.g., open it in their browser).

```py
# (Continuing after detecting auth needed)

if auth_request_function_call_id and auth_config:
    # Get the base authorization URL from the AuthConfig
    base_auth_uri = auth_config.exchanged_auth_credential.oauth2.auth_uri

    if base_auth_uri:
        redirect_uri = 'http://localhost:8000/callback' # MUST match your OAuth client app config
        # Append redirect_uri (use urlencode in production)
        auth_request_uri = base_auth_uri + f'&redirect_uri={redirect_uri}'
        # Now you need to redirect your end user to this auth_request_uri or ask them to open this auth_request_uri in their browser
        # This auth_request_uri should be served by the corresponding auth provider and the end user should login and authorize your application to access their data
        # And then the auth provider will redirect the end user to the redirect_uri you provided
        # Next step: Get this callback URL from the user (or your web server handler)
    else:
         print("ERROR: Auth URI not found in auth_config.")
         # Handle error

```

**Step 3. Handle the Redirect Callback (Client):**

* Your application must have a mechanism (e.g., a web server route at the `redirect_uri`) to receive the user after they authorize the application with the provider.
* The provider redirects the user to your `redirect_uri` and appends an `authorization_code` (and potentially `state`, `scope`) as query parameters to the URL.
* Capture the **full callback URL** from this incoming request.
* (This step happens outside the main agent execution loop, in your web server or equivalent callback handler.)

**Step 4. Send Authentication Result Back to ADK (Client):**

* Once you have the full callback URL (containing the authorization code), retrieve the `auth_request_function_call_id` and the `auth_config` object saved in Client Step 1\.
* Set the captured callback URL in the `exchanged_auth_credential.oauth2.auth_response_uri` field. Also ensure `exchanged_auth_credential.oauth2.redirect_uri` contains the redirect URI you used.
* Create a `types.Content` object containing a `types.Part` with a `types.FunctionResponse`.
      * Set `name` to `"adk_request_credential"`. (Note: This is a special name for ADK to proceed with authentication. Do not use other names.)
      * Set `id` to the `auth_request_function_call_id` you saved.
      * Set `response` to the *serialized* (e.g., `.model_dump()`) updated `AuthConfig` object.
* Call `runner.run_async` **again** for the same session, passing this `FunctionResponse` content as the `new_message`.

```py
# (Continuing after user interaction)

    # Simulate getting the callback URL (e.g., from user paste or web handler)
    auth_response_uri = await get_user_input(
        f'Paste the full callback URL here:\n> '
    )
    auth_response_uri = auth_response_uri.strip() # Clean input

    if not auth_response_uri:
        print("Callback URL not provided. Aborting.")
        return

    # Update the received AuthConfig with the callback details
    auth_config.exchanged_auth_credential.oauth2.auth_response_uri = auth_response_uri
    # Also include the redirect_uri used, as the token exchange might need it
    auth_config.exchanged_auth_credential.oauth2.redirect_uri = redirect_uri

    # Construct the FunctionResponse Content object
    auth_content = types.Content(
        role='user', # Role can be 'user' when sending a FunctionResponse
        parts=[
            types.Part(
                function_response=types.FunctionResponse(
                    id=auth_request_function_call_id,       # Link to the original request
                    name='adk_request_credential', # Special framework function name
                    response=auth_config.model_dump() # Send back the *updated* AuthConfig
                )
            )
        ],
    )

    # --- Resume Execution ---
    print("\nSubmitting authentication details back to the agent...")
    events_async_after_auth = runner.run_async(
        session_id=session.id,
        user_id='user',
        new_message=auth_content, # Send the FunctionResponse back
    )

    # --- Process Final Agent Output ---
    print("\n--- Agent Response after Authentication ---")
    async for event in events_async_after_auth:
        # Process events normally, expecting the tool call to succeed now
        print(event) # Print the full event for inspection

```

!!! note "Note: Authorization response with Resume feature"

    If your ADK agent workflow is configured with the
    [Resume](/runtime/resume/) feature, you also must include
    the Invocation ID (`invocation_id`) parameter with the authorization
    response. The Invocation ID you provide must be the same invocation
    that generated the authorization request, otherwise the system
    starts a new invocation with the authorization response. If your
    agent uses the Resume feature, consider including the Invocation ID
    as a parameter with your authorization request, so it can be included
    with the authorization response. For more details on using the Resume
    feature, see
    [Resume stopped agents](/runtime/resume/).

**Step 5: ADK Handles Token Exchange & Tool Retry and gets Tool result**

* ADK receives the `FunctionResponse` for `adk_request_credential`.
* It uses the information in the updated `AuthConfig` (including the callback URL containing the code) to perform the OAuth **token exchange** with the provider's token endpoint, obtaining the access token (and possibly refresh token).
* ADK internally makes these tokens available by setting them in the session state.
* ADK **automatically retries** the original tool call (the one that initially failed due to missing auth).
* This time, the tool finds the valid tokens (via `tool_context.get_auth_response()`) and successfully executes the authenticated API call.
* The agent receives the actual result from the tool and generates its final response to the user.

---

The sequence diagram of auth response flow, where the ***Agent Client*** sends back the auth response and ADK retries the tool, is as follows:

![Authentication](../assets/auth_part2.svg)

## Journey 2: Building Custom Tools (`FunctionTool`) Requiring Authentication

This section focuses on implementing the authentication logic *inside* your custom Python function when creating a new ADK Tool. We will implement a `FunctionTool` as an example.

### Prerequisites

Your function signature *must* include [`tool_context: ToolContext`](../tools-custom/index.md#tool-context). ADK automatically injects this object, providing access to state and auth mechanisms.

```py
from google.adk.tools import FunctionTool, ToolContext
from typing import Dict

def my_authenticated_tool_function(param1: str, ..., tool_context: ToolContext) -> dict:
    # ... your logic ...
    pass

my_tool = FunctionTool(func=my_authenticated_tool_function)

```

### Authentication Logic within the Tool Function

Implement the following steps inside your function:

**Step 1: Check for Cached & Valid Credentials:**

Inside your tool function, first check if valid credentials (e.g., access/refresh tokens) are already stored from a previous run in this session. Credentials for the current sessions should be stored in `tool_context.invocation_context.session.state` (a dictionary of state) Check existence of existing credentials by checking `tool_context.invocation_context.session.state.get(credential_name, None)`.

```py
from google.oauth2.credentials import Credentials
from google.auth.transport.requests import Request

# Inside your tool function
TOKEN_CACHE_KEY = "my_tool_tokens" # Choose a unique key
SCOPES = ["scope1", "scope2"] # Define required scopes

creds = None
cached_token_info = tool_context.state.get(TOKEN_CACHE_KEY)
if cached_token_info:
    try:
        creds = Credentials.from_authorized_user_info(cached_token_info, SCOPES)
        if not creds.valid and creds.expired and creds.refresh_token:
            creds.refresh(Request())
            tool_context.state[TOKEN_CACHE_KEY] = json.loads(creds.to_json()) # Update cache
        elif not creds.valid:
            creds = None # Invalid, needs re-auth
            tool_context.state[TOKEN_CACHE_KEY] = None
    except Exception as e:
        print(f"Error loading/refreshing cached creds: {e}")
        creds = None
        tool_context.state[TOKEN_CACHE_KEY] = None

if creds and creds.valid:
    # Skip to Step 5: Make Authenticated API Call
    pass
else:
    # Proceed to Step 2...
    pass

```

**Step 2: Check for Auth Response from Client**

* If Step 1 didn't yield valid credentials, check if the client just completed the interactive flow by calling `exchanged_credential = tool_context.get_auth_response()`.
* This returns the updated `exchanged_credential` object sent back by the client (containing the callback URL in `auth_response_uri`).

```py
# Use auth_scheme and auth_credential configured in the tool.
# exchanged_credential: AuthCredential | None

exchanged_credential = tool_context.get_auth_response(AuthConfig(
  auth_scheme=auth_scheme,
  raw_auth_credential=auth_credential,
))
# If exchanged_credential is not None, then there is already an exchanged credential from the auth response.
if exchanged_credential:
   # ADK exchanged the access token already for us
        access_token = exchanged_credential.oauth2.access_token
        refresh_token = exchanged_credential.oauth2.refresh_token
        creds = Credentials(
            token=access_token,
            refresh_token=refresh_token,
            token_uri=auth_scheme.flows.authorizationCode.tokenUrl,
            client_id=auth_credential.oauth2.client_id,
            client_secret=auth_credential.oauth2.client_secret,
            scopes=list(auth_scheme.flows.authorizationCode.scopes.keys()),
        )
    # Cache the token in session state and call the API, skip to step 5
```

**Step 3: Initiate Authentication Request**

If no valid credentials (Step 1.) and no auth response (Step 2.) are found, the tool needs to start the OAuth flow. Define the AuthScheme and initial AuthCredential and call `tool_context.request_credential()`. Return a response indicating authorization is needed.

```py
# Use auth_scheme and auth_credential configured in the tool.

  tool_context.request_credential(AuthConfig(
    auth_scheme=auth_scheme,
    raw_auth_credential=auth_credential,
  ))
  return {'pending': true, 'message': 'Awaiting user authentication.'}

# By setting request_credential, ADK detects a pending authentication event. It pauses execution and ask end user to login.
```

**Step 4: Exchange Authorization Code for Tokens**

ADK automatically generates oauth authorization URL and presents it to your ***Agent Client*** application. your ***Agent Client*** application should follow the same way described in Journey 1 to redirect the user to the authorization URL (with `redirect_uri` appended). Once a user completes the login flow, ADK extracts the authentication callback url from ***Agent Client*** applications, automatically parses the auth code, and generates auth token. At the next Tool call, `tool_context.get_auth_response` in step 2 will contain a valid credential to use in subsequent API calls.

**Step 5: Cache Obtained Credentials**

After successfully obtaining the token from ADK (Step 2) or if the token is still valid (Step 1), **immediately store** the new `Credentials` object in `tool_context.state` (serialized, e.g., as JSON) using your cache key.

```py
# Inside your tool function, after obtaining 'creds' (either refreshed or newly exchanged)
# Cache the new/refreshed tokens
tool_context.state[TOKEN_CACHE_KEY] = json.loads(creds.to_json())
print(f"DEBUG: Cached/updated tokens under key: {TOKEN_CACHE_KEY}")
# Proceed to Step 6 (Make API Call)

```

**Step 6: Make Authenticated API Call**

* Once you have a valid `Credentials` object (`creds` from Step 1 or Step 4), use it to make the actual call to the protected API using the appropriate client library (e.g., `googleapiclient`, `requests`). Pass the `credentials=creds` argument.
* Include error handling, especially for `HttpError` 401/403, which might mean the token expired or was revoked between calls. If you get such an error, consider clearing the cached token (`tool_context.state.pop(...)`) and potentially returning the `auth_required` status again to force re-authentication.

```py
# Inside your tool function, using the valid 'creds' object
# Ensure creds is valid before proceeding
if not creds or not creds.valid:
   return {"status": "error", "error_message": "Cannot proceed without valid credentials."}

try:
   service = build("calendar", "v3", credentials=creds) # Example
   api_result = service.events().list(...).execute()
   # Proceed to Step 7
except Exception as e:
   # Handle API errors (e.g., check for 401/403, maybe clear cache and re-request auth)
   print(f"ERROR: API call failed: {e}")
   return {"status": "error", "error_message": f"API call failed: {e}"}
```

**Step 7: Return Tool Result**

* After a successful API call, process the result into a dictionary format that is useful for the LLM.
* **Crucially, include a**  along with the data.

```py
# Inside your tool function, after successful API call
    processed_result = [...] # Process api_result for the LLM
    return {"status": "success", "data": processed_result}

```

??? "Full Code"

    === "Tools and Agent"

         ```py title="tools_and_agent.py"
         --8<-- "examples/python/snippets/tools/auth/tools_and_agent.py"
         ```
    === "Agent CLI"

         ```py title="agent_cli.py"
         --8<-- "examples/python/snippets/tools/auth/agent_cli.py"
         ```
    === "Helper"

         ```py title="helpers.py"
         --8<-- "examples/python/snippets/tools/auth/helpers.py"
         ```
    === "Spec"

         ```yaml
         openapi: 3.0.1
         info:
         title: Okta User Info API
         version: 1.0.0
         description: |-
            API to retrieve user profile information based on a valid Okta OIDC Access Token.
            Authentication is handled via OpenID Connect with Okta.
         contact:
            name: API Support
            email: support@example.com # Replace with actual contact if available
         servers:
         - url: <substitute with your server name>
            description: Production Environment
         paths:
         /okta-jwt-user-api:
            get:
               summary: Get Authenticated User Info
               description: |-
               Fetches profile details for the user
               operationId: getUserInfo
               tags:
               - User Profile
               security:
               - okta_oidc:
                     - openid
                     - email
                     - profile
               responses:
               '200':
                  description: Successfully retrieved user information.
                  content:
                     application/json:
                     schema:
                        type: object
                        properties:
                           sub:
                           type: string
                           description: Subject identifier for the user.
                           example: "abcdefg"
                           name:
                           type: string
                           description: Full name of the user.
                           example: "Example LastName"
                           locale:
                           type: string
                           description: User's locale, e.g., en-US or en_US.
                           example: "en_US"
                           email:
                           type: string
                           format: email
                           description: User's primary email address.
                           example: "username@example.com"
                           preferred_username:
                           type: string
                           description: Preferred username of the user (often the email).
                           example: "username@example.com"
                           given_name:
                           type: string
                           description: Given name (first name) of the user.
                           example: "Example"
                           family_name:
                           type: string
                           description: Family name (last name) of the user.
                           example: "LastName"
                           zoneinfo:
                           type: string
                           description: User's timezone, e.g., America/Los_Angeles.
                           example: "America/Los_Angeles"
                           updated_at:
                           type: integer
                           format: int64 # Using int64 for Unix timestamp
                           description: Timestamp when the user's profile was last updated (Unix epoch time).
                           example: 1743617719
                           email_verified:
                           type: boolean
                           description: Indicates if the user's email address has been verified.
                           example: true
                        required:
                           - sub
                           - name
                           - locale
                           - email
                           - preferred_username
                           - given_name
                           - family_name
                           - zoneinfo
                           - updated_at
                           - email_verified
               '401':
                  description: Unauthorized. The provided Bearer token is missing, invalid, or expired.
                  content:
                     application/json:
                     schema:
                        $ref: '#/components/schemas/Error'
               '403':
                  description: Forbidden. The provided token does not have the required scopes or permissions to access this resource.
                  content:
                     application/json:
                     schema:
                        $ref: '#/components/schemas/Error'
         components:
         securitySchemes:
            okta_oidc:
               type: openIdConnect
               description: Authentication via Okta using OpenID Connect. Requires a Bearer Access Token.
               openIdConnectUrl: https://your-endpoint.okta.com/.well-known/openid-configuration
         schemas:
            Error:
               type: object
               properties:
               code:
                  type: string
                  description: An error code.
               message:
                  type: string
                  description: A human-readable error message.
               required:
                  - code
                  - message
         ```
