Integrate Cline with Live Sage 300 Data via CData Connect AI

Cline is an autonomous AI coding agent that runs inside modern IDEs such as VS Code and Cursor. It enables developers to build agent-driven workflows that can reason through tasks, execute actions, and interact with external systems directly from the editor using a structured execution model.

By integrating Cline with CData Connect AI through the built-in MCP (Model Context Protocol) Server, the agent gains the ability to query, analyze, and act on live Sage 300 data in real time. This integration bridges Cline's in-IDE agent framework with the governed enterprise connectivity of CData Connect AI, ensuring all data access runs securely against authorized sources without manual data movement.

This article outlines the steps to configure Sage 300 connectivity in Connect AI, generate the required personal access token, register the Connect AI MCP Server in Cline, and verify that the agent can successfully interact with live Sage 300 data from within the IDE.

Step 1: Configure Sage 300 connectivity for Cline

Connectivity to Sage 300 from Cline is made possible through CData Connect AI's Remote MCP Server. To interact with Sage 300 data from Cline, start by creating and configuring a Sage 300 connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select Sage 300 from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage 300.

   Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.

   • Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the option under Security Groups (per each module required).
   • Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
   • Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.

   Authenticate to Sage 300 using Basic authentication.

   Connect Using Basic Authentication

   You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.

   • Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
   • User: Set this to the username of your account.
   • Password: Set this to the password of your account.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Cline. It is best practice to create a separate PAT for each integration to maintain granular access control.

1. Click the gear icon () at the top right of the Connect AI app to open Settings
2. On the Settings page, go to the Access Tokens section and click Create PAT
3. Give the PAT a descriptive name and click Create

4. Copy the token when displayed and store it securely. It will not be shown again

With the Sage 300 connection configured and a PAT generated, Cline can now connect to Sage 300 data through the CData Connect Ai.

Step 2: Install and set up Cline

Cline is distributed as an IDE extension and can be installed in environments such as VS Code or Cursor. In this example, Cursor is used, but the steps are identical for supported IDEs.

1. Open Cursor and install the Cline extension from the Extensions Marketplace
2. Complete the initial Cline setup flow, including model selection and permission prompts
3. After setup is complete, the Cline agent panel opens automatically inside the IDE

Step 3: Add the Connect AI Remote MCP Server

Once Cline is running, add the CData Connect AI Remote MCP Server so the agent can access live Sage 300 data through Connect AI.

1. In the Cline panel, click MCP Servers
2. Open Remote Servers and click Edit Configuration
3. This opens a JSON configuration file. Paste the configuration below

   {
     "mcpServers": {
       "mcp": {
         "url": "https://mcp.cloud.cdata.com/mcp",
         "type": "streamableHttp",
         "headers": {
           "Authorization": "Basic your_email:your_PAT"
         },
         "disabled": false,
         "autoApprove": []
       }
     }
   }
   

   Note: Cline will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier. For example, [email protected]:ABC123...XYZ789 and add the value for the Authorization header like, Basic [email protected]:ABC123...XYZ789.

   
4. Save the file and return to the MCP Servers screen to confirm the server is listed and enabled

Step 4: Query live data from Cline

With the MCP server registered, Cline can now interact with live data sources exposed by Connect AI.

1. Click the icon in the Cline panel to start a New Task/Chat
2. At the bottom of the chat window, confirm that the configured MCP server is selected
3. Start interacting with the agent by entering prompts such as:
   • List connections
   • Show schemas for a catalog
   • Query recent records from Sage 300 data
   

Cline is now fully configured to access and query live Sage 300 data through the CData Connect AI Remote MCP Server, enabling real-time, data-driven workflows directly from your IDE.

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