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⇱ How to Connect API Data to Gemini Enterprise via CData Connect AI

How to Connect API Data to Gemini Enterprise via CData Connect AI

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Connect CData Connect AI Remote MCP to Gemini Enterprise to securely read and take actions on live API data in real time using natural language.

Gemini Enterprise is Google's enterprise AI assistant, available as part of Google Workspace. With native support for Custom MCP Server data stores, Gemini Enterprise can be extended to query and act on live enterprise data via the Model Context Protocol (MCP). When combined with CData Connect AI Remote MCP, Gemini Enterprise can interact with API data in real time using natural language — without data replication or custom integration logic.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to API data via a single managed MCP endpoint. The CData Connect AI Remote MCP Server enables secure communication between Gemini Enterprise and API, allowing users to ask questions and take actions on live API data through natural language prompts.

This article explains how to connect Gemini Enterprise to live API data through CData Connect AI by creating a Custom MCP Server data store — giving users access to API data directly from the Gemini Enterprise chat interface.

Prerequisites

  1. A CData Connect AI account with at least one active connection (e.g., API)
  2. A Gemini Enterprise account (trial available)
  3. A Google Cloud project with billing enabled
  4. The Google Cloud CLI installed and configured
  5. In your Google Cloud account:
    • Override the organization policy for Custom MCP data stores (learn more).
    • Grant the Discovery Engine Editor role to the administrator (learn more).

Step 1: Configure your API connectivity for Gemini Enterprise

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

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. 👁 Adding a Connection
  2. Select "API" from the Add Connection panel
    3. 👁 Selecting a data source
  3. Enter the necessary authentication properties to connect to your API.

    To connect to your API, configure the following properties on the Global Settings page:

    • In Authentication, select the Type and fill in the required properties
    • In Headers, add the required HTTP headers for your API
    • In Pagination, select the Type and fill in the required properties

    After the configuring the global settings, navigate to the Tables to add tables. For each table you wish to add:

    1. Click "+ Add"
    2. Set the Name for the table
    3. Set Request URL to the API endpoint you wish to work with 👁 Setting the Request URL (Harvest is shown)
    4. (Optional) In Parameters, add the required URL Parameters for your API endpoint
    5. (Optional) In Headers, add the required HTTP headers for the API endpoint
    6. In Table Data click " Configure"
    7. Review the response from the API and click "Next" 👁 Reviewing the API response (Harvest is shown)
    8. Select which element to use as the Repeated Elements and which elements to use as Columns and click "Next" 👁 Configuring the schema based on the API response(Harvest is shown)
    9. Preview the tabular model of the API response and click "Confirm" 👁 Previewing the tabular model of the API response (Harvest is shown)
  4. Click Save & Test
  5. Navigate to the Permissions tab in the Add your API Connection page and update the User-based permissions. 👁 Updating permissions

Create an OAuth App in CData Connect AI

Gemini Enterprise uses OAuth 2.0 Authorization Code with PKCE to authenticate users against the CData Connect AI MCP Server. This requires creating a user-based OAuth App in your CData Connect AI account.

  1. Click the Gear icon () in the top-right corner of Connect AI to open Settings.
  2. Navigate to OAuth Apps and click + Create App. The Create OAuth App dialog appears.
  3. Enter the following settings:
    • Name — Enter a descriptive name (e.g., GeminiEnterpriseOAuth).
    • Authentication Flow — Select User-based (Authorization Code).
    • Callback URL — Enter https://vertexaisearch.cloud.google.com/oauth-redirect.
    👁 Creating a new OAuth App in CData Connect AI
  4. Click Confirm. CData Connect AI creates the OAuth App and generates a Client ID and Client Secret.
  5. Copy both the Client ID and Client Secret values. You will need them in Step 5. 👁 Copying the Client ID and Client Secret

With the connection configured and an OAuth App created, we are ready to create the custom MCP server data store in Gemini Enterprise.

Step 2: Create the custom MCP server data store

  1. Open Gemini Enterprise and navigate to the Data stores screen.
  2. Click Create data store.
  3. On the Select a data source page, enter Custom MCP Server in the Search sources field. The Custom MCP Server card displays.
  4. Click Add MCP server. The MCP Server Configuration page displays.
  5. In the Authentication settings section, enter values in the following required fields:
    • MCP Server URL: https://mcp.cloud.cdata.com/mcp
    • Authorization URL: https://cloud-login.cdata.com/authorize
    • Token URL: https://cloud-login.cdata.com/oauth/token
    • Client ID and Client Secret: From the OAuth App created in Step 1
    👁 Entering MCP Server configuration details
  6. Click Login, and complete the sign-in.
  7. Click Continue, and the Advanced options section opens.

  8. In the MCP Server Description field, enter a description that helps Gemini Enterprise understand what the server does and when to use it. For more information, see Write effective MCP server descriptions and instructions.

  9. Click Continue.

  10. In the Configure your data connector section, select the Location of your data connector from the Multi-region field list.

  11. In Your data connector name, enter a name for your data store.

  12. Click Create. Gemini Enterprise creates your data store and displays your data stores on the Data Stores page.

    Note: By default, no tools or actions from your custom MCP servers are enabled. You must enable the tools or actions.

Step 3: Enable actions

After creating the custom MCP server data store, you must enable at least one tool or action before it can be used in Gemini Enterprise.

  1. Go to your custom MCP server data store.

  2. Open the Actions tab and select Reload custom actions to reauthenticate.

    Note: This action performs a tools/list call on the MCP server to retrieve available tools, which are then displayed on the screen.

  3. Select the actions to enable.
  4. Click Enable actions. 👁 Enabling actions

Step 4: Connect the MCP server data store to a Gemini Enterprise app

After creating the custom MCP server data store and enabling actions, you must connect the data store to a Gemini Enterprise app before it can be used.

  1. In the Google Cloud console, go to the Gemini Enterprise page.
  2. From the navigation menu, click Apps.
  3. Select the Gemini Enterprise app where you want to connect your data store.
  4. From the navigation menu of the app, click Connected data sources.
  5. Click Add existing data stores and select your data store.
  6. Click Connect. 👁 Connecting data store

Step 5: Query live API data with natural language

With the data store connected, Gemini Enterprise users can interact with live API data using natural language from the Gemini Enterprise web application. Each user authenticates with their own Connect AI credentials via the OAuth flow on first use.

  1. Open Gemini Enterprise, click Connections and authorize CData Connect AI. 👁 Authorizing CData Connect AI
  2. Ask natural language questions about your API data:
    • "Show me all API data from the last 30 days"
    • "What are the top records in API data by revenue?"
    • "List all active API data and their current status"
    • "Summarize API data activity for this quarter"
  3. The agent automatically discovers available connections in Connect AI, identifies the most relevant API connection, generates SQL, and returns results — all without requiring the user to write queries or understand the underlying data structure.

Get CData Connect AI

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from Gemini Enterprise and other AI platforms, try CData Connect AI today!