Build Confluence-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 Confluence, configuring the connection to Confluence, connecting the Code Assist MCP add-on to Gemini Code Assist, and querying live Confluence 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 Confluence has been installed
4. Access to Confluence

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 Confluence

1. To begin, download the CData Code Assist MCP for Confluence
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 Confluence.

Step 2: Configure the connection to Confluence

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

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for Confluence" 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_confluence") and click OK

4. Enter the appropriate connection properties in the configuration wizard

   Obtaining an API Token

   An API token is necessary for account authentication. To generate one, login to your Atlassian account and navigate to API tokens > Create API token. The generated token will be displayed.

   Connect Using a Confluence Cloud Account

   To connect to a Cloud account, provide the following (Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.):

   • User: The user which will be used to authenticate with the Confluence server.
   • APIToken: The API Token associated with the currently authenticated user.
   • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.

   Connect Using a Confluence Server Instance

   To connect to a Server instance, provide the following:

   • User: The user which will be used to authenticate with the Confluence instance.
   • Password: The password which will be used to authenticate with the Confluence server.
   • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.
   
5. Click Connect to authenticate with Confluence
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_confluence").

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

Step 4: Query live Confluence 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 Confluence Code Assist MCP add-on should appear with a green connection indicator
3. Ask questions about Confluence data using natural language. For example:

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

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

   "Write a function to retrieve records from the Pages table where Key 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 Confluence, 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 Confluence data during development. When you're ready to move to production, CData Confluence 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.