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

Step 1: Download and install the CData API Driver for MCP Server

1. To begin, download the CData API Driver for MCP Server 👁 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 PDFMonkey.

Step 2: Configure the connection to PDFMonkey

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

   NOTE: If the wizard does not open automatically, search for "CData API Driver for MCP Server" 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_api") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   Using API Key Authentication

   PdfMonkey uses API key authentication. To obtain an API key:

   1. Log in to your PdfMonkey account at https://app.pdfmonkey.io
   2. Navigate to your account settings
   3. Open the API Key page
   4. Copy your API key

   After obtaining your API key, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   Set the following in the ProfileSettings connection property:
   • APIKey: Set this to your PdfMonkey API key.

   Example Connection String

   Profile=C:\profiles\PdfMonkey.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key"
   

   Connecting to PdfMonkey

   Once the authentication is configured, you can connect to PdfMonkey and query data from any of the available tables such as CurrentUser, DocumentCards, Documents, DocumentTemplateCards, and DocumentTemplates.

   👁 Configuring the MCP Server add-on connection
   
5. Click Connect to authenticate with PDFMonkey
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_api": {
 "command": "C:\Program Files\CData\CData API Driver for MCP Server\jre\bin\java.exe",
 "args": [
 "-Dfile.encoding=UTF-8",
 "-jar",
 "C:\Program Files\CData\CData API Driver for MCP Server\lib\cdata.mcp.api.jar",
 "cdata_api"
 ]
 }
 }
}

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_api").

Option 2: Copy the MCP configuration from the CData API Driver for MCP Server 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 PDFMonkey 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 PDFMonkey data using natural language. For example:

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

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

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

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

Build with MCP Server. Deploy with CData Drivers.

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