VOOZH about

URL: https://www.cdata.com/kb/tech/azure-cloud-cursor.rst

⇱ Integrate Cursor with Live Azure Table Data via CData Connect AI


Integrate Cursor with Live Azure Table Data via CData Connect AI

πŸ‘ Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Cursor to securely access and act on live Azure Table data from within the editor.

Cursor is an AI-powered code editor that embeds conversational and agent-style assistance alongside your development workflow. By extending Cursor with MCP (Model Context Protocol) tools, you can give its AI agents secure access to external systems such as APIs and databases.

Integrating Cursor with CData Connect AI via the built-in MCP server allows the editor's AI to query, analyze, and act on live Azure Table data without copying data into the IDE. The result is a development experience where you can chat with your governed enterprise data directly from Cursor.

This article outlines how to configure Azure Table connectivity in Connect AI, generate the required access token, register Connect AI's MCP Server in Cursor, and then use the AI chat pane to explore live Azure Table data.

Step 1: Configure Azure Table connectivity for Cursor

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. πŸ‘ Adding a connection in Connect AI
  3. Select Azure Table from the Add Connection panel
  4. πŸ‘ Selecting data source
  5. Enter the necessary authentication properties to connect to Azure Table.

    Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

    πŸ‘ Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. πŸ‘ Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Cursor. 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. πŸ‘ Creating a new PAT
  5. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use

With the Azure Table connection configured and a PAT generated, Cursor can now connect to Azure Table data through Connect AI.

Step 2: Configure Connect AI in Cursor

Next, configure Cursor to use Connect AI. Cursor reads MCP configuration from an mcp.json file in the user configuration directory and exposes the registered servers under the Tools & MCP settings. Once configured, Cursor's AI chat can call the tools exposed by CData Connect AI.

  1. Download the Cursor desktop application and complete the sign-up flow for your account
  2. From the top menu, click Settings to open the settings panel πŸ‘ Opening Cursor Settings
  3. In the left navigation, open the Tools & MCP tab and click Add Custom MCP πŸ‘ Tools & MCP tab with Add Custom MCP
  4. Cursor opens an mcp.json file in the editor
  5. Add the following configuration. Make sure to base64-encode your email:PAT before inserting into the header:
    {
     "mcpServers": {
     "cdata-mcp": {
     "url": "https://mcp.cloud.cdata.com/mcp",
     "headers": {
     "Authorization": "Basic your_base64_encoded_email_PAT"
     }
     }
     }
    }
    		
    πŸ‘ Configuring mcp.json with Connect AI
  6. Save the file
  7. Return to Settings and then select Tools & MCP. You can now see cdata-mcp enabled with an active indicator πŸ‘ Connect AI enabled

Step 3: Chat with CData Connect AI from Cursor

  1. From the top bar, click Toggle AI Pane to open the chat window πŸ‘ Opening the AI pane
  2. Test the connection by entering "List connections"
  3. You can also run queries like "Query Azure Table data and list the high priority accounts" πŸ‘ Querying Azure Table data from Connect AI

Cursor is now fully integrated with the CData Connect AI MCP Server and can act on live Azure Table data directly from the editor.

Get CData Connect AI

To access hundreds of SaaS, Big Data, and NoSQL sources directly from your development tools, try CData Connect AI today!