Integrate Google's Antigravity Agent with Live Sage X3 Cloud Data via CData Connect AI

Antigravity is an AI-native development environment designed around autonomous and semi-autonomous agents. It allows developers to run agent-driven workflows directly inside the editor, combining planning, execution, and tool usage in a single interface.

By integrating Antigravity with CData Connect AI through the built-in MCP (Model Context Protocol) Server, agents gain governed, real-time access to live Sage X3 Cloud data. This enables Antigravity agents to explore schemas, query data, and perform actions without manual data movement or custom API wiring.

This article explains how to configure Sage X3 Cloud connectivity in Connect AI, generate the required access token, register CData Connect AI in Antigravity, and validate the integration by querying live Sage X3 Cloud data from an agent-driven workflow.

Step 1: Configure Sage X3 Cloud connectivity for Antigravity

Connectivity to Sage X3 Cloud from Antigravity is made possible through CData Connect AI's Remote MCP Server. To interact with Sage X3 Cloud data from Antigravity, start by creating and configuring a Sage X3 Cloud connection in CData Connect AI.

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

2. Select Sage X3 Cloud from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage X3 Cloud.

   Sage X3 Cloud uses the OAuth 2.0 Client Credentials flow, and an X-API-Key is also required for API access. Set AuthScheme to OAuth and specify the following connection properties:

   • URL: The base URL of your Sage X3 Cloud instance.
   • OAuthAccessTokenUrl: The OAuth token endpoint (e.g., https://your-auth-domain/oauth/token).
   • OAuthClientId: Your OAuth application client ID.
   • OAuthClientSecret: Your OAuth application client secret.
   • Audience: The API audience value for the token request.
   • XAPIKey: The X-API-Key provided by your Sage X3 Cloud administrator.
   • Folder: The Sage X3 folder name (e.g., SEED). This folder is used as the default schema.
   • Folders (optional): A comma-separated list of Sage X3 folders (e.g., SEED,PERF). Each folder is exposed as a separate schema, so you can query across folders with the Schema.Table syntax.

   The driver obtains an access token with the Client Credentials flow and sends it with the X-API-Key on every API request. With InitiateOAuth set to GETANDREFRESH (the default), the driver acquires and refreshes the token automatically.

   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Antigravity. 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. Copy the token when displayed and store it securely. It will not be shown again

With the Sage X3 Cloud connection configured and a PAT generated, Antigravity can now connect to Sage X3 Cloud data through CData Connect AI.

Step 2: Configure Connect AI in Antigravity

Next, register Connect AI in Antigravity. Antigravity reads MCP server definitions from a raw configuration file, allowing agents to dynamically discover and invoke the sources exposed by Connect AI.

1. Download the Antigravity desktop application and sign in using your Google account
2. During the initial setup flow, select Agent-driven development when prompted. This mode enables autonomous agents with tool execution capabilities
3. Once you have completed the Antigravity setup and the IDE is open, you can access the built-in agent interface to manage MCP servers. From the top menu, click Toggle Agent or press Ctrl + Alt + B to open the agent panel
4. Once the agent panel opens, click the "..." and select MCP Servers from the dropdown
5. Select Manage MCP Servers from the MCP Store, and click View raw config to open the MCP configuration file
6. Paste the following json into the file:

   {
       "mcpServers": {
           "cdata-mcp": {
               "serverUrl": "https://mcp.cloud.cdata.com/mcp",
               "headers": {
                   "Authorization": "Basic your_base64_encoded_email_PAT",
                   "Content-Type": "application/json"
               }
           }
       }
   }
   		

   Note: Antigravity will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier and base64 encode the value. For example, given username and PAT like [email protected]:ABC123...XYZ789, the value for the Authorization header is something like: Basic dXNlckBteWRvbWFpbjphSzkvbVB4Mi9Rcjd2TjQvTHc4Qi96WTZqQzMvRnQ1SGcxL0RzMFVlL01iWHdKdg==

   
7. Save the configuration file
8. Return to the Manage MCP Servers view and click Refresh to load the new MCP server

Step 3: Query live Sage X3 Cloud data from Antigravity agent

With the MCP server registered, Antigravity agents can now interact with your live data sources exposed by Connect AI to explore schemas and run queries.

1. Open the agent panel again using Toggle Agent
2. Start a new conversation in the agent chat
3. Start interacting with the agent by entering prompts such as:
   • List all catalogs in my cdata-mcp connection.
   • Show schemas and tables available for Sage X3 Cloud.
   • Query the top 3 records from a table in Sage X3 Cloud data.
   

At this point, your Antigravity agent communicates with the CData Connect AI MCP Server and retrieves live Sage X3 Cloud data through remote MCP tools.

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