Build Amazon S3-Powered Applications in GitHub Copilot with CData Code Assist MCP

GitHub Copilot is an AI-powered coding assistant that integrates directly into Visual Studio Code and other IDEs. With support for MCP, GitHub Copilot can connect to local tools and enterprise data sources, enabling natural language interaction with live systems during development.

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.

In this article, we guide you through installing the CData Code Assist MCP for Amazon S3, configuring the connection to Amazon S3, connecting the Code Assist MCP add-on to GitHub Copilot, and querying live Amazon S3 data from within Visual Studio Code.

Prerequisites

• Visual Studio Code is installed on your machine
• GitHub Copilot Chat extension is enabled in Visual Studio Code
• CData Code Assist MCP for Amazon S3 has been installed

Step 1: Download and install the CData Code Assist MCP for Amazon S3

1. To begin, download the CData Code Assist MCP for Amazon S3 👁 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 Amazon S3.

Step 2: Configure the connection to Amazon S3

1. After installation, open the CData Code Assist MCP for Amazon S3 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 Amazon S3" 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_amazons3") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

   Note: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

   For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

   👁 Configuring the Code Assist MCP add-on connection
   
5. Click Connect to authenticate with Amazon S3
6. Click Save & Test to finalize the connection 👁 Saving and testing the Code Assist MCP add-on configuration
   

This process creates a .mcp configuration file that GitHub Copilot 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 GitHub Copilot.

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

1. Download and install Visual Studio Code and enable the GitHub Copilot Chat extension

Option 1: Manually add the MCP configuration

1. Open or create the mcp.json file:
   • For global configuration: %%APPDATA%%/Roaming/Code/User/mcp.json
   • For project-specific configuration:
2. Add the JSON code shown below and save the file

{
 "servers": {
 "cdata_amazons3": {
 "command": "C:\Program Files\CData\CData Code Assist MCP for Amazon S3\jre\bin\java.exe",
 "args": [
 "-Dfile.encoding=UTF-8",
 "-jar",
 "C:\Program Files\CData\CData Code Assist MCP for Amazon S3\lib\cdata.mcp.amazons3.jar",
 "cdata_amazons3"
 ]
 }
 }
}

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_amazons3").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Amazon S3 UI

1. After saving and testing your connection in the configuration wizard, click Next 👁 Selecting 'Next'
   
2. Select Github Copilot from the AI MCP Tool dropdown 👁 Choosing GitHub Copilot as the AI MCP tool
   
3. Follow the MCP Client Instructions to create the required configuration file 👁 MCP configuration instructions for GitHub Copilot
   
4. Copy the displayed JSON code and paste it into your configuration file

Step 4: Query live Amazon S3 data in GitHub Copilot

1. Launch Visual Studio Code and open the GitHub Copilot Chat interface. Select the tool icon to enable the configured Code Assist MCP add-on 👁 Enabling the CData Code Assist MCP add-on in GitHub Copilot
   
2. Ask questions about your Amazon S3 data using natural language. For example:

   "List all tables available in my Amazon S3 data data connection."

   👁 Querying live data from GitHub Copilot
   
3. Start building with natural language prompts:

   For my project, data from the ObjectsACL is very important. Pull data from the most important columns like Name and OwnerId.
   

GitHub Copilot is now fully integrated with CData Code Assist MCP for Amazon S3 and can use the MCP tools to explore schemas and execute live queries against Amazon S3.

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 Amazon S3 data during development. When you're ready to move to production, CData Amazon S3 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.