How to Query Live Lakebase Data in Claude Desktop

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData Code Assist MCP, these capabilities expand exponentially.

CData Code Assist MCP provides schema-aware context to AI tools — whether you're using it for AI-assisted code generation in IDEs like Cursor, or for querying live data through chat interfaces like Claude Desktop.

In this article, we guide the reader through installing CData Code Assist MCP for Lakebase, configuring the connection to Lakebase, and asking questions of the data in Claude Desktop.

Prerequisites

You need to download Claude Desktop (download) and create an account before continuing.

Overview

Here's a quick overview of the steps:

1. Download and install the CData Code Assist MCP for Lakebase
2. Configure the connection to Lakebase
3. Ask questions about the data in Claude Desktop

Step 1: Download and install CData Code Assist MCP

1. To begin, navigate to https://www.cdata.com/solutions/codeassist/ and download the CData Code Assist MCP for Lakebase. 👁 Downloading the CData Code Assist MCP installer
   
2. Find and double-click the installer to begin the installation. 👁 Running the installer for CData Code Assist MCP (Google Sheets is shown.)
   
3. Follow the prompts to complete the installation. 👁 Completing the CData Code Assist MCP installation (Google Sheets is shown).
   

When the installation is complete, you are ready to configure Code Assist MCP by connecting to Lakebase.

Step 2: Configure the connection to Lakebase

1. After installation, the Code Assist MCP configuration wizard should open automatically. 👁 The Code Assist MCP configuration wizard.
   

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP" in the Windows search bar and double-click the application. 👁 Opening the Code Assist MCP configuration wizard (Google Sheets is shown).
   

2. Click the dropdown menu in MCP Configuration > Configuration Name and select "
3. Name the configuration (e.g. "cdatalakebase") and click "OK."

   NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.

   👁 Naming the configuration.
   

4. Connecting to Lakebase

   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.

   Enter the appropriate connection properties in the configuration wizard.

   👁 Configuring the Server to connect with a specific Spreadsheet.
   
5. Click "Connect" to authenticate with Lakebase through OAuth. 👁 Authenticating with Google
   

   NOTE: The configuration wizard should open your browser and ask you to sign into Lakebase. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).

   👁 Running the configuration wizard with elevated permissions.
   
6. Finally, click "Save Configuration" to save the configuration. 👁 Saving the Code Assist MCP configuration.
   

   NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start Code Assist MCP when the Claude Desktop client starts.

With Code Assist MCP configured, you are ready to start asking questions of your live data from Claude.

Step 3: Ask AI for answers from live Lakebase data

Now that we have installed Code Assist MCP and configured a connection, we are ready to start with Lakebase data in Claude Desktop.

1. Open Claude Desktop. It may take a moment for Code Assist MCP to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar). 👁 The MCP servers menu showing available connections in Claude Desktop
   

   You can individually enable and disable specific tools by clicking on the server name. 👁 The expanded tool list for Code Assist MCP in Claude Desktop
   

2. Now that you have connected, you can ask Claude questions about the Lakebase data. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the Lakebase data to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.

   👁 Claude Desktop displaying a quantitative analysis of live data
   

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.