How to set up SAML SSO and still use OAuth for programmatic API access

What You Will Build

• You will configure a Genesys Cloud environment to use SAML 2.0 for human user login while maintaining a separate OAuth Client for server-to-server API access.
• You will implement a Python script using the purecloudplatformclientv2 SDK to authenticate via OAuth 2.0 Client Credentials flow, bypassing the SAML login screen entirely.
• You will verify that the API token grants access to protected resources like User Management and Analytics, proving the separation of concerns between human and machine authentication.

Prerequisites

• Genesys Cloud Account: An organization with administrative privileges to configure SSO and create OAuth clients.
• SAML Identity Provider (IdP): A working IdP (e.g., Okta, Azure AD, OneLogin) configured with Genesys Cloud as a Service Provider (SP).
• Python 3.8+: Installed with pip package manager.
• SDK: purecloudplatformclientv2 (Genesys Cloud Python SDK).
• Required Scopes: For the OAuth client, you will need specific scopes depending on the API calls. For this tutorial, we will use user:read and analytics:query.

Authentication Setup

The core architectural principle here is separation. SAML handles identity for humans (who they are, what groups they belong to). OAuth Client Credentials handles authorization for machines (what the application can do).

When you enable SAML SSO in Genesys Cloud, the standard OAuth Authorization Code flow (where a user logs in via a browser) is often disabled or redirected to the IdP. However, the Client Credentials Grant flow remains available and is the recommended method for backend services, batch jobs, and automated integrations.

Step 1: Create the Machine-to-Machine OAuth Client

Before writing code, you must create the credentials that your script will use. This client is not tied to a specific user; it is tied to the application itself.

1. Log in to the Genesys Cloud Admin Portal.
2. Navigate to Setup > Security > OAuth Clients.
3. Click Add OAuth Client.
4. Fill in the details:
   • Name: API-Backend-Service
   • Description: Programmatic access for analytics and user management
   • Client Type: Select Confidential (or Public if running in a browser-less environment without secret storage, though Confidential is more secure).
5. Scopes: Add the required scopes. For this tutorial, add:
   • user:read
   • analytics:query
   • pur:read (if you need to read purecloud configuration)
6. Save the client.
7. Copy the Client ID and Client Secret. You will need these for the Python script.

Note: Do not assign this client to a specific user. It operates independently. If you need the API to act “as” a specific user (impersonation), you would use the user:impersonate scope and include the user’s ID in the token request, but for most backend tasks, the client’s own permissions are sufficient.

Step 2: Install Dependencies

Open your terminal and install the official Genesys Cloud Python SDK.

pip install purecloudplatformclientv2

Implementation

Step 1: Initialize the Platform Client with OAuth

The Genesys Cloud Python SDK simplifies the OAuth flow. Instead of manually constructing POST requests to /oauth/token, you use the PlatformClient object.

Create a file named genesys_oauth_demo.py.

import os
import sys
from purecloudplatformclientv2 import (
    PlatformClient,
    Configuration,
    UserApi,
    AnalyticsApi
)
from purecloudplatformclientv2.rest import ApiException

# Configuration constants
# In production, use environment variables or a secrets manager
CLIENT_ID = os.environ.get('GENESYS_CLIENT_ID', 'your_client_id_here')
CLIENT_SECRET = os.environ.get('GENESYS_CLIENT_SECRET', 'your_client_secret_here')

def create_platform_client() -> PlatformClient:
    """
    Initializes the Genesys Cloud PlatformClient using OAuth Client Credentials.
    This bypasses SAML login entirely.
    """
    # Create the platform client instance
    platform_client = PlatformClient()

    # Configure the OAuth flow
    # The SDK automatically handles the token request to /oauth/token
    # and caches the token until expiration.
    try:
        platform_client.set_oauth_client_credentials(
            client_id=CLIENT_ID,
            client_secret=CLIENT_SECRET
        )
        print("OAuth Client Credentials configured successfully.")
        return platform_client
    except Exception as e:
        print(f"Failed to configure OAuth client: {e}")
        sys.exit(1)

if __name__ == "__main__":
    client = create_platform_client()
    print("Platform Client initialized.")

Why this works:
The set_oauth_client_credentials method triggers a background request to the Genesys Cloud OAuth endpoint. It exchanges the client_id and client_secret for an access token. This token is stored in memory. When you make subsequent API calls, the SDK automatically attaches the Authorization: Bearer <token> header. If the token expires (typically after 1 hour), the SDK automatically refreshes it using the same client credentials.

Step 2: Verify Authentication with a User API Call

Now that you have an authenticated client, you should verify it works by calling a protected endpoint. We will use the UserApi to list users. This requires the user:read scope.

def list_users(platform_client: PlatformClient):
    """
    Retrieves a list of users using the UserApi.
    Demonstrates that the OAuth token has the 'user:read' scope.
    """
    user_api = UserApi(platform_client)

    try:
        # Get the first page of users
        # pageSize=5 is for demonstration; default is usually 25
        response = user_api.post_users_query(
            body={"pageSize": 5}
        )

        print(f"\n--- User List Result ---")
        print(f"Total users found: {response.total}")
        print(f"Page size: {response.page_size}")
        
        if response.entities:
            print("First 5 users:")
            for user in response.entities:
                print(f"  - ID: {user.id}, Name: {user.name}, Email: {user.email}")
        else:
            print("No users found or insufficient permissions.")

    except ApiException as e:
        print(f"API Exception when calling UserApi.post_users_query: {e}")
        if e.status == 401:
            print("Authentication failed. Check Client ID/Secret.")
        elif e.status == 403:
            print("Forbidden. Check if 'user:read' scope is assigned to the OAuth Client.")
        elif e.status == 429:
            print("Rate limited. Implement exponential backoff.")

Key Insight:
Notice we do not log in as “John Doe”. The API call is made by the “API-Backend-Service” client. If that client does not have the user:read scope, you will get a 403 Forbidden error, even if the SAML users in the system have that permission. This is the critical distinction: OAuth Client permissions are independent of User permissions.

Step 3: Query Analytics Data

To demonstrate a more complex use case, we will query conversation analytics. This requires the analytics:query scope.

def query_analytics(platform_client: PlatformClient):
    """
    Queries conversation analytics for the last 24 hours.
    Requires 'analytics:query' scope.
    """
    analytics_api = AnalyticsApi(platform_client)

    # Define the query body
    # We are querying for conversation details
    query_body = {
        "groupBy": ["wrapUpCode"],
        "interval": "PT1H",
        "dateFrom": "2023-10-01T00:00:00Z", # Example date, adjust as needed
        "dateTo": "2023-10-02T00:00:00Z",
        "aggregations": [
            {
                "name": "conversationCount",
                "type": "count"
            }
        ]
    }

    try:
        # Note: The actual endpoint for analytics queries is often POST /api/v2/analytics/conversations/details/query
        # The SDK method name may vary slightly depending on the version, but post_analytics_conversations_details_query is standard.
        response = analytics_api.post_analytics_conversations_details_query(
            body=query_body
        )

        print(f"\n--- Analytics Result ---")
        print(f"Query completed successfully.")
        print(f"Number of intervals returned: {len(response.intervals) if response.intervals else 0}")
        
        # Print the first interval if available
        if response.intervals:
            first_interval = response.intervals[0]
            print(f"First interval: {first_interval.start} to {first_interval.end}")
            if first_interval.aggregations:
                for agg in first_interval.aggregations:
                    print(f"  Aggregation: {agg.name} = {agg.value}")

    except ApiException as e:
        print(f"API Exception when calling AnalyticsApi: {e}")
        if e.status == 403:
            print("Forbidden. Ensure 'analytics:query' scope is added to the OAuth Client.")

Complete Working Example

Here is the full script, combining initialization, user listing, and analytics querying.

import os
import sys
import json
from purecloudplatformclientv2 import (
    PlatformClient,
    UserApi,
    AnalyticsApi
)
from purecloudplatformclientv2.rest import ApiException

# --- Configuration ---
# Replace these with your actual OAuth Client ID and Secret
# Best practice: Load from environment variables
CLIENT_ID = os.environ.get('GENESYS_CLIENT_ID')
CLIENT_SECRET = os.environ.get('GENESYS_CLIENT_SECRET')

if not CLIENT_ID or not CLIENT_SECRET:
    print("Error: GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables are required.")
    sys.exit(1)

def init_client() -> PlatformClient:
    """
    Initializes the Genesys Cloud PlatformClient using OAuth Client Credentials.
    """
    platform_client = PlatformClient()
    
    # Set the OAuth credentials
    # This handles the token acquisition and caching automatically
    platform_client.set_oauth_client_credentials(
        client_id=CLIENT_ID,
        client_secret=CLIENT_SECRET
    )
    
    return platform_client

def fetch_users(client: PlatformClient):
    """
    Fetches a list of users to verify 'user:read' scope.
    """
    user_api = UserApi(client)
    
    try:
        # Query for users
        response = user_api.post_users_query(body={"pageSize": 3})
        
        print("\n=== User Verification ===")
        print(f"Total Users: {response.total}")
        for user in response.entities:
            print(f"  ID: {user.id}, Name: {user.name}")
            
    except ApiException as e:
        print(f"User API Error ({e.status}): {e.reason}")
        if e.body:
            print(f"Response Body: {e.body}")

def fetch_analytics(client: PlatformClient):
    """
    Fetches analytics data to verify 'analytics:query' scope.
    """
    analytics_api = AnalyticsApi(client)
    
    # Define a simple analytics query
    # Note: Adjust dateFrom and dateTo to a valid range in your org
    query_body = {
        "groupBy": ["queueId"],
        "interval": "PT1D",
        "dateFrom": "2023-01-01T00:00:00Z",
        "dateTo": "2023-01-02T00:00:00Z",
        "aggregations": [
            {
                "name": "offerAnsweredCount",
                "type": "sum"
            }
        ]
    }
    
    try:
        response = analytics_api.post_analytics_conversations_details_query(body=query_body)
        
        print("\n=== Analytics Verification ===")
        print(f"Query ID: {response.id if hasattr(response, 'id') else 'N/A'}")
        print(f"Intervals returned: {len(response.intervals) if response.intervals else 0}")
        
    except ApiException as e:
        print(f"Analytics API Error ({e.status}): {e.reason}")
        if e.body:
            print(f"Response Body: {e.body}")

def main():
    print("Initializing Genesys Cloud Platform Client...")
    try:
        client = init_client()
        print("Client initialized successfully.")
        
        # Run verification steps
        fetch_users(client)
        fetch_analytics(client)
        
        print("\n=== Script Completed Successfully ===")
        
    except Exception as e:
        print(f"Unexpected error: {e}")
        sys.exit(1)

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

Cause:
The client_id or client_secret is incorrect, or the OAuth client has been deleted/disabled.

Fix:

1. Verify the Client ID and Secret in the Genesys Cloud Admin Portal under Setup > Security > OAuth Clients.
2. Ensure there are no trailing spaces in your environment variables.
3. Check if the client is enabled. If it was disabled, re-enable it.

Error: 403 Forbidden

Cause:
The OAuth client does not have the required scope for the API endpoint you are calling.

Fix:

1. Identify the required scope for the endpoint. For UserApi.post_users_query, it is user:read. For AnalyticsApi, it is analytics:query.
2. Go to the OAuth Client configuration in Genesys Cloud.
3. Add the missing scope to the list.
4. Important: You must regenerate the access token. The SDK handles this automatically on the next call, but if you cached the token manually, you must discard it.

Error: 429 Too Many Requests

Cause:
You have exceeded the rate limit for the API endpoint. Genesys Cloud enforces strict rate limits per OAuth client.

Fix:
Implement exponential backoff. The Python SDK does not automatically retry 429s, so you must handle this in your code.

import time

def api_call_with_retry(api_method, max_retries=3, initial_delay=1):
    for attempt in range(max_retries):
        try:
            return api_method()
        except ApiException as e:
            if e.status == 429:
                delay = initial_delay * (2 ** attempt)
                print(f"Rate limited. Retrying in {delay} seconds...")
                time.sleep(delay)
            else:
                raise e
    raise Exception("Max retries exceeded")

Error: “Invalid Grant” or “Unauthorized Client”

Cause:
The OAuth client is configured as Public but you are sending a client_secret, or vice versa. Or, the client is not allowed to use the Client Credentials grant type.

Fix:
Ensure the OAuth Client Type in Genesys Cloud matches your implementation. If you are using client_secret, the client must be Confidential. If you are using PKCE or Authorization Code flow without a secret, it can be Public. For backend services, Confidential is standard.

Official References

• Genesys Cloud OAuth 2.0 Documentation
• Python SDK Reference
• User API Documentation
• Analytics API Documentation