Connecting GenSpark with PingOne Data via CData Connect AI MCP Server

GenSpark is built for developers and enterprise teams who want to create intelligent, conversational AI experiences powered by real-time data. It's flexible tooling and agentic capabilities make it easy to integrate LLMs, automate complex workflows, and build interactive applications that adapt to user intent. However, when these AI interactions require data beyond local context or predefined APIs, many implementations fall back on custom middleware, manual integrations, or scheduled ETL pipelines to sync information into local stores. This introduces unnecessary complexity, increases maintenance overhead, slows response times, and limits the real-time intelligence your GenSpark agents can provide.

CData Connect AI eliminates these barriers by delivering live, secure connectivity to more than 300 enterprise applications, databases, ERPs, and analytics platforms. Through CData Connect AI remote Model Context Protocol (MCP) Server, GenSpark agents can query, read, and act on real-time enterprise data without replication or custom integration code. The result is grounded, accurate responses, faster reasoning, and automated, cross-system decision-making all with stronger governance and fewer moving parts.

This guide outlines the steps required to configure CData Connect AI MCP connectivity, register the MCP Server in GenSpark, and enable your GenSpark agents to work seamlessly with live enterprise data in real time.

Prerequisites

Before starting, ensure you have:

1. A CData Connect AI account
2. Access to GenSpark
3. Access to PingOne

Credentials checklist

Ensure you have these credentials ready for the connection:

1. USERNAME: Your CData email login
2. PAT: Connect AI, go to Settings and click on Access Tokens (copy once)
3. MCP_BASE_URL: https://mcp.cloud.cdata.com/mcp

Step 1: Configure PingOne connectivity for GenSpark

Connectivity to PingOne from GenSpark is made possible through CData Connect AI Remote MCP. To interact with PingOne data from GenSpark, 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 GenSpark. 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 GenSpark.

Step 2: Configure MCP Server in GenSpark

1. Log in to GenSpark
2. Below the chat interface, click the Tools icon

3. Select Add new MCP server


4. Fill in the server configuration:

   NOTE: Use Basic authentication, where you combine your Connect AI email address (e.g. [email protected]) with the PAT you generated earlier (e.g. AbC123...xYz890) with a colon (:) in the Authorization header.

   
   

   Field	Value
   Name	CData MCP Server (or any name you prefer)
   Server Type	SteamableHttp
   Server URL	https://mcp.cloud.cdata.com/mcp
   Request Header	{"Authorization": "Basic [email protected]:AbC123...xYz890"}

5. Click Add Server

Once added, GenSpark will automatically load all MCP tools exposed through your Connect AI workspace.

Step 3: Query data in GenSpark

In GenSpark chat interface enter any sample prompt:

List the tools present in CData Connect AI MCP Server.

Build real-time, data-aware agents with GenSpark and CData

GenSpark and CData Connect AI together enable intelligent, AI-driven workflows where agents can securely access live enterprise data and operate with real-time awareness without ETL pipelines, data sync jobs, or custom integration logic. This streamlined approach delivers stronger governance, lower operational overhead, and faster, more grounded responses from your AI tools.

Start your free trial today to see how CData can empower GenSpark with live, secure access to hundreds of external systems.