Build Lakebase-Powered Applications in Gemini Code Assist with CData Code Assist MCP

Gemini Code Assist is an AI-powered coding companion that integrates intelligent code generation into everyday development workflows. With support for MCP, Gemini Code Assist can connect to live enterprise data sources directly from Visual Studio Code, enabling natural language interaction with structured data without switching context or manually writing data access code.

Model Context Protocol (MCP) is an open standard for connecting LLM clients to external services through structured tool interfaces. MCP servers expose capabilities such as schema discovery and live querying, allowing AI agents to retrieve and reason over real-time data safely and consistently.

This guide walks through installing the CData Code Assist MCP for Lakebase, configuring the connection to Lakebase, connecting the Code Assist MCP add-on to Gemini Code Assist, and querying live Lakebase data from within the editor.

Prerequisites

Before starting, ensure the following requirements are met:

1. Visual Studio Code is installed on the machine
2. Gemini Code Assist extension is enabled in Visual Studio Code
3. CData Code Assist MCP for Lakebase has been installed
4. Access to Lakebase

Note: Gemini Code Assist must already be set up and functional in Visual Studio Code before configuring MCP servers. MCP servers are accessed when Gemini Code Assist is running in Agent mode.

Step 1: Download and install the CData Code Assist MCP for Lakebase

1. To begin, download the CData Code Assist MCP for Lakebase
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation

When the installation is complete, the Code Assist MCP add-on is ready for configuration by connecting to Lakebase.

Step 2: Configure the connection to Lakebase

1. After installation, open the CData Code Assist MCP for Lakebase configuration wizard

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for Lakebase" in the Windows search bar and open the application.

   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one
3. Name the configuration (e.g. "cdata_lakebase") and click OK

4. Enter the appropriate connection properties in the configuration wizard

   To connect to Databricks Lakebase, start by setting the following properties:
   • DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
   • Server: The host name or IP address of the server hosting the Lakebase database.
   • Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
   • Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.

   OAuth Client Authentication

   To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:

   1. Create and configure a new service principal
   2. Assign permissions to the service principal
   3. Create an OAuth secret for the service principal

   For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.

   OAuth PKCE Authentication

   To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:

   • AuthScheme: OAuthPKCE.
   • User: The authenticating user's user ID.

   For more information, refer to the Help documentation.

   
5. Click Connect to authenticate with Lakebase through OAuth
6. Then, click Save Configuration to save the Code Assist MCP add-on

This process creates a .mcp configuration file that Gemini Code Assist will reference when launching the Code Assist MCP add-on. With the Code Assist MCP add-on configured, it is ready to connect to Gemini Code Assist.

Step 3: Connect the Code Assist MCP add-on to Gemini Code Assist

1. Ensure Visual Studio Code is installed and the Gemini Code Assist extension is enabled
2. From the configuration wizard, click Next after saving and testing the connection
3. Select Gemini Code Assist from the AI MCP Tool dropdown
4. Click Copy JSON to copy the generated MCP configuration to the clipboard
5. Paste the copied JSON into the appropriate configuration file based on the desired scope:
   • User-level: Configuration applies across all projects for the current user
   • Workspace-level: Configuration applies only to the current workspace or project

   NOTE: The configuration includes the path to Java 17+ executable and the CData Code Assist MCP add-on JAR file. The final argument must match the MCP configuration name saved in the wizard (e.g. "cdata_lakebase").

6. Save the configuration file and restart Visual Studio Code if necessary

Step 4: Query live Lakebase data in Gemini Code Assist

1. Open Visual Studio Code and select Gemini Code Assist in the activity bar
2. Enter /mcp in the chat prompt to verify the connection status. The Lakebase Code Assist MCP add-on should appear with a green connection indicator
3. Ask questions about Lakebase data using natural language. For example:

   "Provide the list of all tables available in my Lakebase data connection."

   
4. Generate code that works with live Lakebase data. For example:

   "Write a function to retrieve records from the Orders table where ShipName matches a given value."

   

Gemini Code Assist is now fully integrated with the CData Code Assist MCP add-on and can use the MCP tools exposed to explore schemas, execute live queries against Lakebase, and generate data-aware code.

Build with Code Assist MCP. Deploy with CData Drivers.

Download Code Assist MCP for free and give your AI tools schema-aware access to live Lakebase data during development. When you're ready to move to production, CData Lakebase Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.