Build Suadeo-Powered Applications in GitHub Copilot with CData MCP Server

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 MCP Server for Suadeo, configuring the connection to Suadeo, connecting the MCP Server add-on to GitHub Copilot, and querying live Suadeo 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 MCP Server for Suadeo has been installed

Step 1: Download and install the CData MCP Server for Suadeo

1. To begin, download the CData MCP Server for Suadeo 👁 Downloading the CData MCP Server 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 MCP Server add-on installation
   

When the installation is complete, you are ready to configure your MCP Server add-on by connecting to Suadeo.

Step 2: Configure the connection to Suadeo

1. After installation, open the CData MCP Server for Suadeo configuration wizard 👁 The CData MCP Server add-on configuration wizard
   

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

   👁 Opening the CData MCP Server 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_suadeo") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   The driver uses the OAuth 2.0 Resource Owner Password Credentials (ROPC) grant to authenticate to Suadeo. Authentication occurs directly using your credentials; there is no browser-based authorization flow or refresh token.

   Set the following connection properties:

   • URL: The base URL of your Suadeo instance.
   • User: Your Suadeo username.
   • Password: Your Suadeo password.
   • AuthenticationName: The name identifier for the authentication configuration in your Suadeo instance. Different authentication names can be configured for different environments or use cases.

   When you connect, the driver sends your credentials to the Suadeo OAuth token endpoint, receives an access token, and uses it for all subsequent requests. A new access token is obtained automatically when needed during the session.

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

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

Step 3: Connect the MCP Server 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_suadeo": {
 "command": "C:\Program Files\CData\CData MCP Server for Suadeo\jre\bin\java.exe",
 "args": [
 "-Dfile.encoding=UTF-8",
 "-jar",
 "C:\Program Files\CData\CData MCP Server for Suadeo\lib\cdata.mcp.suadeo.jar",
 "cdata_suadeo"
 ]
 }
 }
}

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

Option 2: Copy the MCP configuration from the CData MCP Server for Suadeo 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 Suadeo data in GitHub Copilot

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

   "List all tables available in my Suadeo data data connection."

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

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

GitHub Copilot is now fully integrated with CData MCP Server for Suadeo and can use the MCP tools to explore schemas and execute live queries against Suadeo.

Build with MCP Server. Deploy with CData Drivers.

Download CData MCP Server for Suadeo for free and give your AI tools schema-aware access to live Suadeo data during development. When you're ready to move to production, CData Suadeo 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.