Build BigQuery-Powered Applications in Claude Code with CData Code Assist MCP

Claude Code is an AI-powered command line tool that enables agentic coding workflows. With support for MCP, Claude Code can connect to local tools and enterprise data sources directly from your terminal, enabling natural language interaction with live systems without switching context.

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.

The following steps cover installing the CData Code Assist MCP for Google BigQuery, configuring the connection to BigQuery, connecting the Code Assist MCP add-on to Claude Code, and querying live BigQuery data from within the terminal.

Getting Started

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

1. To begin, download the CData Code Assist MCP for Google BigQuery 👁 Downloading the CData Code Assist MCP add-on installer
   
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation 👁 Completing the CData Code Assist MCP add-on installation
   

When the installation is complete, you are ready to configure your Code Assist MCP add-on by connecting to BigQuery.

Step 2: Configure the connection to BigQuery

1. After installation, open the CData Code Assist MCP for Google BigQuery configuration wizard 👁 The CData Code Assist MCP add-on configuration wizard
   

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

   👁 Opening the CData Code Assist MCP add-on configuration wizard (Google Sheets is shown).
   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one 👁 Creating a new configuration
   
3. Name the configuration (e.g. "cdata_googlebigquery") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.

   OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, register an application to obtain the OAuth JWT values.

   In addition to the OAuth values, specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

   👁 Configuring the Code Assist MCP add-on connection
   
5. Click Connect to authenticate with BigQuery through OAuth
6. Then, click Save Configuration to save the Code Assist MCP add-on 👁 Saving the Code Assist MCP add-on configuration
   

This process creates a .mcp configuration file that Claude Code will reference when launching the Code Assist MCP add-on. Now with your Code Assist MCP add-on configured, you are ready to connect it to Claude Code.

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

1. Install the Claude Code CLI using the terminal
2. Open the Claude Code configuration file at ~/.config/claude-code/config.json (or the location shown after initialization)

Option 1: Manually add the MCP configuration

1. Open the mcp.json file in your preferred editor
2. Add the code shown below

{
"mcpServers" : {
 "cdata_googlebigquery" : {
 "type" : "stdio",
 "command" : "C:\Program Files\CData\CData Code Assist MCP for Google BigQuery\jre\bin\java.exe",
 "args" : [ "-Dfile.encoding=UTF-8", "-jar", "C:\Program Files\CData\CData Code Assist MCP for Google BigQuery/lib/cdata.mcp.googlebigquery.jar", "cdata_googlebigquery" ], 
 "env" : {}
 }
}
}

NOTE: The command value should point to your Java 17+ java.exe executable, and the JAR path should point to the installed CData Code Assist MCP add-on .jar file. The final argument must match the MCP configuration name you saved in the CData configuration wizard (e.g. "cdata_googlebigquery").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Google BigQuery UI

1. After saving and testing your connection in the configuration wizard, click Next
👁 Selecting 'Next'

2. Select Claude Code from the AI MCP Tool dropdown
👁 Choosing the required AI MCP tool

3. Click Copy JSON to copy the generated MCP configuration to your clipboard
👁 Copying the MCP configuration

4. Paste the copied JSON into the mcp.json file

Step 4: Verify connection in Claude Code

Claude Code provides tools to verify the connection is active before building.

1. Open a terminal and navigate to your project directory. Run the command claude mcp list
2. Check that your configuration name appears with a Connected status
👁 Checking the connection status

3. Start Claude Code by running claude
4. Inside the Claude Code session, type /mcp to view active servers 👁 Viewing active MCP servers
   

Step 5: Query live BigQuery data in Claude Code

With the connection verified, you can now use natural language prompts to query and work with live BigQuery data.

1. Prompt Claude Code to review the instructions for your MCP connection to ensure it has all the appropriate context when writing code 👁 Reviewing MCP connection instructions
   
2. Start building with natural language prompts! For example:

   For my project, data from the Orders is very important. Pull data from the most important columns like OrderName and Freight.

Claude Code will use the MCP add-on to connect to BigQuery, retrieve the requested data, and provide results directly in your terminal

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 BigQuery data during development. When you're ready to move to production, CData BigQuery 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.