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

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 AlloyDB 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 AlloyDB data via a single managed MCP endpoint. The CData Connect AI Remote MCP Server enables secure communication between Gemini Enterprise and AlloyDB, allowing users to ask questions and take actions on live AlloyDB data through natural language prompts.

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

Prerequisites

1. A CData Connect AI account with at least one active connection (e.g., AlloyDB)
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 AlloyDB connectivity for Gemini Enterprise

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

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

2. Select "AlloyDB" from the Add Connection panel

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

   The following connection properties are usually required in order to connect to AlloyDB.

   • Server: The host name or IP of the server hosting the AlloyDB database.
   • User: The user which will be used to authenticate with the AlloyDB server.
   • Password: The password which will be used to authenticate with the AlloyDB server.

   You can also optionally set the following:

   • Database: The database to connect to when connecting to the AlloyDB Server. If this is not set, the user's default database will be used.
   • Port: The port of the server hosting the AlloyDB database. This property is set to 5432 by default.

   Authenticating with Standard Authentication

   Standard authentication (using the user/password combination supplied earlier) is the default form of authentication.

   No further action is required to leverage Standard Authentication to connect.

   Authenticating with pg_hba.conf Auth Schemes

   There are additional methods of authentication available which must be enabled in the pg_hba.conf file on the AlloyDB server.

   Find instructions about authentication setup on the AlloyDB Server here.

   Authenticating with MD5 Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to md5.

   Authenticating with SASL Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to scram-sha-256.

   Authenticating with Kerberos

   The authentication with Kerberos is initiated by AlloyDB Server when the ∏ is trying to connect to it. You should set up Kerberos on the AlloyDB Server to activate this authentication method. Once you have Kerberos authentication set up on the AlloyDB Server, see the Kerberos section of the help documentation for details on how to authenticate with Kerberos.

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

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
   
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.

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.

Step 5: Query live AlloyDB data with natural language

With the data store connected, Gemini Enterprise users can interact with live AlloyDB 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.
2. Ask natural language questions about your AlloyDB data:
   • "Show me all AlloyDB data from the last 30 days"
   • "What are the top records in AlloyDB data by revenue?"
   • "List all active AlloyDB data and their current status"
   • "Summarize AlloyDB data activity for this quarter"
3. The agent automatically discovers available connections in Connect AI, identifies the most relevant AlloyDB connection, generates SQL, and returns results — all without requiring the user to write queries or understand the underlying data structure.

Get CData Connect AI

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