Build SQL Analysis Services-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 SQL Analysis Services, configuring the connection to SQL Analysis Services, connecting the Code Assist MCP add-on to GitHub Copilot, and querying live SQL Analysis Services 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 SQL Analysis Services has been installed

Step 1: Download and install the CData Code Assist MCP for SQL Analysis Services

1. To begin, download the CData Code Assist MCP for SQL Analysis Services
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, you are ready to configure your Code Assist MCP add-on by connecting to SQL Analysis Services.

Step 2: Configure the connection to SQL Analysis Services

1. After installation, open the CData Code Assist MCP for SQL Analysis Services configuration wizard

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for SQL Analysis Services" 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_ssas") and click OK

4. Enter the appropriate connection properties in the configuration wizard

   To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

   To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

   • HTTP Authentication

     Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

   • Windows (NTLM)

     Set the Windows User and Password and set AuthScheme to "NTLM".

   • Kerberos and Kerberos Delegation

     To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

   • SSL/TLS:

     By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

   You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

   See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

   
5. Click Connect to authenticate with SQL Analysis Services
6. Click Save & Test to finalize the connection

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: /.vscode/mcp.json
2. Add the JSON code shown below and save the file

{
  "servers": {
    "cdata_ssas": {
      "command": "C:\Program Files\CData\CData Code Assist MCP for SQL Analysis Services\jre\bin\java.exe",
      "args": [
        "-Dfile.encoding=UTF-8",
        "-jar",
        "C:\Program Files\CData\CData Code Assist MCP for SQL Analysis Services\lib\cdata.mcp.ssas.jar",
        "cdata_ssas"
      ]
    }
  }
}

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_ssas").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for SQL Analysis Services UI

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

Step 4: Query live SQL Analysis Services 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
2. Ask questions about your SQL Analysis Services data using natural language. For example:

   "List all tables available in my SQL Analysis Services data data connection."

   
3. Start building with natural language prompts:

   For my project, data from the Adventure_Works is very important. Pull data from the most important columns like Fiscal_Year and Sales_Amount.
   

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

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 SQL Analysis Services data during development. When you're ready to move to production, CData SQL Analysis Services 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.