Integrate OpenCode with Live PingOne Data via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Use the CData Connect AI Remote MCP Server to enable OpenCode to securely access and query live PingOne data from within your AI coding agent.

OpenCode is an open source AI coding agent that connects to a wide range of LLM providers. It supports the model context protocol (MCP), allowing you to configure local or remote MCP servers in its configuration files to add external tools and data sources and give the agent access to live data.

By integrating OpenCode with CData Connect AI through the built-in MCP Server, OpenCode gains governed, real-time access to live PingOne data. You can list catalogs, explore schemas, and query records from PingOne data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure PingOne connectivity in Connect AI, generate the required personal access token, install OpenCode, add the Connect AI MCP Server in the project configuration file, configure an LLM provider, and verify the integration by querying live PingOne data from OpenCode.

Step 1: Configure PingOne connectivity for OpenCode

Connectivity to PingOne from OpenCode is made possible through Connect AI's Remote MCP Server. To interact with PingOne data from OpenCode, start by creating and configuring a PingOne connection in Connect AI.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a connection in Connect AI
  3. Select PingOne from the Add Connection panel
  4. Selecting data source
  5. 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.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from OpenCode. It is best practice to create a separate PAT for each integration to maintain granular access control.

  1. Click the gear icon () at the top right of the Connect AI app to open Settings
  2. On the Settings page, go to the Access Tokens section and click Create PAT
  3. Give the PAT a descriptive name and click Create
  4. Creating a new PAT
  5. Copy the token when displayed and store it securely. It will not be shown again

With the PingOne connection configured and a PAT generated, OpenCode can now connect to PingOne data through Connect AI.

Step 2: Install OpenCode and configure the Connect AI MCP Server

Next, install OpenCode, add the Connect AI Remote MCP Server in your project configuration file, and configure an LLM provider so the agent can discover and call live data tools through Connect AI.

  1. Download and install OpenCode by following the official installation guide
  2. Create a new folder for your project, or open an existing project directory
  3. In the root of that directory, create a file named opencode.json and paste the following configuration:
    {
      "$schema": "https://opencode.ai/config.json",
      "mcp": {
        "cdata-connect-ai": {
          "type": "remote",
          "url": "https://mcp.cloud.cdata.com/mcp",
          "enabled": true,
          "oauth": false,
          "headers": {
            "Authorization": "Basic your_base64_encoded_email_PAT"
          },
          "timeout": 30000
        }
      }
    }
    		

    Note: OpenCode will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

  4. Open the project directory in OpenCode. Select the project from the project dropdown, or click Add project to point OpenCode at the folder that contains opencode.json Opening the project directory in OpenCode
  5. Configure an LLM provider so the agent can interpret prompts and call MCP tools. Open the model selector (Ctrl + '), choose a provider such as OpenAI, Anthropic, or Google, and enter your API key Selecting an LLM provider and model in OpenCode

With the MCP server added in opencode.json and an LLM provider configured, OpenCode is ready to query live PingOne data through Connect AI.

Step 3: Query live PingOne data from OpenCode

With the integration complete, use OpenCode to interact with live PingOne data through natural language prompts handled by the configured LLM.

  1. In a new session, type a prompt in the chat input, for example:
    • Use the cdata-connect-ai tools to list all available catalogs
    • Show the available schemas and tables for PingOne
    • Query the top 5 records from a table in PingOne
  2. OpenCode calls the Connect AI MCP Server and returns live results from PingOne data Querying live data from OpenCode

At this point, OpenCode communicates with the Connect AI MCP Server and retrieves live PingOne data through remote MCP tools directly from your AI coding agent.

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