How to Connect Flowise AI Agents to Live PingOne Data via CData Connect AI

Integrate Flowise AI with the CData Connect AI MCP Server to enable agents to securely query and act on live PingOne data without replication.

Flowise AI is an open-source, no-code tool for building AI workflows and custom agents visually. Its drag-and-drop interface allows you to integrate large language models (LLMs) with APIs, databases, and external systems effortlessly.

CData Connect AI enables real-time connectivity to hundreds of enterprise data sources. Through its Model Context Protocol (MCP) server, CData Connect AI bridges Flowise agents with live PingOne securely and efficiently, no data replication required. By combining Flowise AI's intuitive agent builder with CData's MCP integration, users can create agents capable of fetching, analyzing, and acting upon live PingOne data directly within Flowise AI workflows.

This guide shows you how to connect Flowise AI to CData Connect AI MCP, set up credentials, and enable your agents to query live PingOne data in real time.

Step 1: Configure PingOne Connectivity for Flowise

Connectivity to PingOne from Flowise AI is made possible through CData Connect AI's Remote MCP Server. To interact with PingOne data from Flowise AI, 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. 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

Once the connection is established, PingOne data is now accessible in CData Connect AI and ready to be used with MCP enabled tools.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Flowise AI. 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, Flowise AI can now connect to PingOne data through Connect AI.

Step 2: Configure Connect AI credentials in Flowise AI

Log in to Flowise AI workspace to set up the integration.

Add OpenAI credentials

  1. Navigate to Credentials and choose Add Credential
  2. Click Add credential
  3. Select OpenAI API from the dropdown
  4. Provide a name (e.g., OpenAI_Key) and paste the API key
  5. Adding OpenAI credentials in Flowise

Add the PAT variable

  1. Navigate to Variables and Add Variable
  2. Navigate to Variables
  3. Set Variable Name (e.g., PAT), choose Static as type, and set the Value to Base64-encoded username:PAT
  4. Click Add to save the variable
  5. Adding PAT as variable in Flowise

Step 3: Build the agent in Flowise AI

  1. Go to Agent Flows, select Add New
  2. Agent Flow page
  3. Click the "+" icon to add a new node and choose Agent and drag the agent to the workflow
  4. Adding agent node in Flowise
  5. Connect the Start node to the Agent node
  6. Connecting agent nodes in Flowise

Configure agent settings

Double-click on the Agent node and fill in the details:

  • Model: select ChatOpenAI or preferred model (e.g., gpt-4o-mini)
  • Connect Credential: Select OpenAI API key credential which was created earlier
  • Streaming: Enabled
Fill in the details for Agent Node

Add the custom MCP tool

  1. Under Tools, click Add Tool and choose Custom MCP
  2. Fill in the JSON parameters as shown below:
 
{
  "url": "https://mcp.cloud.cdata.com/mcp",
  "headers": {
    "Authorization": "Basic {{$vars.PAT}}"
  }
}
Configuring custom MCP tool in Flowise

Click the refresh icon to load available MCP actions. Once actions are listed, now Flowise agent is successfully connected to CData Connect AI MCP.

Step 4: Test and query live PingOne data in Flowise

  1. Open the Chat tab in Flowise
  2. Type a query such as "Show top 10 records from PingOne data table"
  3. Observe that responses are fetched in real time via the CData Connect AI MCP connection
  4. Testing live queries in Flowise

With the workflow run completed, Flowise demonstrates successful retrieval of Salesforce data through the CData Connect AI MCP server, with the MCP Client node providing the ability to ask questions, retrieve records, and perform actions on the data.


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