Integrate Cline with Live Azure Data Lake Storage 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 Azure Data Lake Storage 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 Azure Data Lake Storage 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 Azure Data Lake Storage data from within the IDE.

Step 1: Configure Azure Data Lake Storage connectivity for Cline

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

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

2. Select Azure Data Lake Storage from the Add Connection panel

3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the .
   2. Select "Entra ID" (formerly Azure AD).
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
   
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 Azure Data Lake Storage connection configured and a PAT generated, Cline can now connect to Azure Data Lake Storage 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 Azure Data Lake Storage 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 Azure Data Lake Storage data
   

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

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