Integrate Cursor with Live JSON Data via CData Connect AI

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 JSON services 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 JSON 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 JSON services.

Step 1: Configure JSON connectivity for Cursor

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

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

2. Select JSON from the Add Connection panel

3. Enter the necessary authentication properties to connect to JSON.

   See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

   After setting the URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.

   The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your JSON data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling JSON Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   
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 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. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use

With the JSON connection configured and a PAT generated, Cursor can now connect to JSON services 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
3. In the left navigation, open the Tools & MCP tab and click 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"
         }
       }
     }
   }
   		

   
6. Save the file
7. Return to Settings and then select Tools & MCP. You can now see cdata-mcp enabled with an active indicator

Step 3: Chat with CData Connect AI from Cursor

1. From the top bar, click Toggle AI Pane to open the chat window
2. Test the connection by entering "List connections"
3. You can also run queries like "Query JSON services and list the high priority accounts"

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

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