How to Connect to Live PingOne Data from Gemini CLI (via CData Connect AI)

Gemini CLI is a command-line interface tool that provides direct access to Google's Gemini AI models for code generation, text analysis, and conversational AI capabilities. When combined with CData Connect AI Remote MCP, you can leverage Gemini CLI to interact with your PingOne data in real-time through natural language queries. This article outlines the process of connecting to PingOne using Connect AI Remote MCP and configuring Gemini CLI to interact with your PingOne data.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to PingOne data. The CData Connect AI Remote MCP Server enables secure communication between Gemini CLI and PingOne. This allows you to ask questions and take actions on your PingOne data using natural language through Gemini CLI, all without the need for data replication to a natively supported database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to PingOne. This leverages server-side processing to swiftly deliver the requested PingOne data.

In this article, we show how to configure Gemini CLI to conversationally explore (or Vibe Query) your data using natural language. With Connect AI you can query and interact with live PingOne data, plus hundreds of other sources.

Step 1: Configure PingOne Connectivity for Gemini CLI

Connectivity to PingOne from Gemini CLI is made possible through CData Connect AI Remote MCP. To interact with PingOne data from Gemini CLI, we start by creating and configuring a PingOne connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "PingOne" from the Add Connection panel

3. Enter the necessary authentication properties to connect to PingOne.

   To connect to PingOne, configure these properties:

   • Region: The region where the data for your PingOne organization is being hosted.
   • AuthScheme: The type of authentication to use when connecting to PingOne.
   • Either WorkerAppEnvironmentId (required when using the default PingOne domain) or AuthorizationServerURL, configured as described below.

   Configuring WorkerAppEnvironmentId

   WorkerAppEnvironmentId is the ID of the PingOne environment in which your Worker application resides. This parameter is used only when the environment is using the default PingOne domain (auth.pingone). It is configured after you have created the custom OAuth application you will use to authenticate to PingOne, as described in Creating a Custom OAuth Application in the Help documentation.

   First, find the value for this property:

   1. From the home page of your PingOne organization, move to the navigation sidebar and click Environments.
   2. Find the environment in which you have created your custom OAuth/Worker application (usually Administrators), and click Manage Environment. The environment's home page displays.
   3. In the environment's home page navigation sidebar, click Applications.
   4. Find your OAuth or Worker application details in the list.
   5. Copy the value in the Environment ID field. It should look similar to:
      

      WorkerAppEnvironmentId='11e96fc7-aa4d-4a60-8196-9acf91424eca'

   Now set WorkerAppEnvironmentId to the value of the Environment ID field.

   Configuring AuthorizationServerURL

   AuthorizationServerURL is the base URL of the PingOne authorization server for the environment where your application is located. This property is only used when you have set up a custom domain for the environment, as described in the PingOne platform API documentation. See Custom Domains.

   Authenticating to PingOne with OAuth

   PingOne supports both OAuth and OAuthClient authentication. In addition to performing the configuration steps described above, there are two more steps to complete to support OAuth or OAuthCliet authentication:

   • Create and configure a custom OAuth application, as described in Creating a Custom OAuth Application in the Help documentation.
   • To ensure that the driver can access the entities in Data Model, confirm that you have configured the correct roles for the admin user/worker application you will be using, as described in Administrator Roles in the Help documentation.
   • Set the appropriate properties for the authscheme and authflow of your choice, as described in the following subsections.

   OAuth (Authorization Code grant)

   Set AuthScheme to OAuth.

   Desktop Applications

   Get and Refresh the OAuth Access Token

   After setting the following, you are ready to connect:

   • InitiateOAuth: GETANDREFRESH. To avoid the need to repeat the OAuth exchange and manually setting the OAuthAccessToken each time you connect, use InitiateOAuth.
   • OAuthClientId: The Client ID you obtained when you created your custom OAuth application.
   • OAuthClientSecret: The Client Secret you obtained when you created your custom OAuth application.
   • CallbackURL: The redirect URI you defined when you registered your custom OAuth application. For example: https://localhost:3333

   When you connect, the driver opens PingOne's OAuth endpoint in your default browser. Log in and grant permissions to the application. The driver then completes the OAuth process:

   1. The driver obtains an access token from PingOne and uses it to request data.
   2. The OAuth values are saved in the location specified in OAuthSettingsLocation, to be persisted across connections.

   The driver refreshes the access token automatically when it expires.

   For other OAuth methods, including Web Applications, Headless Machines, or Client Credentials Grant, refer to the Help documentation.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add PingOne Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Gemini CLI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to PingOne data from Gemini CLI.

Step 2: Configure Gemini CLI for CData Connect AI

Follow these steps to configure Gemini CLI to connect to CData Connect AI:

1. Ensure Gemini CLI is installed on your system. If not, install it using npm:

   npm install -g @google-gemini/cli

2. Locate your Gemini CLI settings file. If the file doesn't exist, create it:
   • Linux/Unix/Mac: ~/.gemini/settings.json
   • Windows: %USERPROFILE%\.gemini\settings.json
3. Add the CData Connect AI Remote MCP Server to the mcpServers object in your settings file. Replace YOUR_EMAIL and YOUR_PAT with your Connect AI email address and the PAT created previously:

   {
     "mcpServers": {
       "cdata-connect-cloud": {
         "httpUrl": "https://mcp.cloud.cdata.com/mcp",
         "headers": {
           "Authorization": "Basic YOUR_EMAIL:YOUR_PAT"
         }
       }
     }
   }    

   For example, if your email is [email protected] and your PAT is Uu90pt5vEO..., the Authorization header would be:

   "Authorization": "Basic [email protected]:Uu90pt5vEO..."

4. Save the settings file. Gemini CLI will now use the CData Connect AI MCP Server for data operations.

Step 3: Query Live PingOne Data with Natural Language

With Gemini CLI configured and connected to CData Connect AI, you can now interact with your PingOne data using natural language queries. The MCP integration allows you to ask questions and receive responses from the PingOne data source in real-time.

Start using Gemini CLI to explore your data:

1. Open your terminal and start a Gemini CLI session:

   gemini

2. You can now use natural language to query your PingOne data. For example:
   • "Show me all customers from the last 30 days"
   • "What are my top performing products?"
   • "Analyze sales trends for Q4"
   • "List all active projects with their current status"
3. Gemini CLI will automatically translate your natural language queries into appropriate SQL queries and execute them against your PingOne data through the CData Connect AI MCP Server.

The combination of Gemini CLI's natural language processing capabilities and CData Connect AI's robust data connectivity enables you to explore and analyze your PingOne data without writing complex SQL queries or needing deep technical knowledge of the underlying data structure.

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