Integrate Cursor with Live Databricks 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 Databricks 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 Databricks 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 Databricks data.
About Databricks Data Integration
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
- Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
- Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
- Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
- Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Getting Started
Step 1: Configure Databricks connectivity for Cursor
Connectivity to Databricks from Cursor is made possible through CData Connect AI's Remote MCP Server. To interact with Databricks data from Cursor, start by creating and configuring a Databricks connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select Databricks from the Add Connection panel
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Enter the necessary authentication properties to connect to Databricks.
To connect to a Databricks cluster, set the properties as described below.
Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
- Server: Set to the Server Hostname of your Databricks cluster.
- HTTPPath: Set to the HTTP Path of your Databricks cluster.
- Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
- Click Save & Test
- 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.
- Click the gear icon () at the top right of the Connect AI app to open Settings
- On the Settings page, go to the Access Tokens section and click Create PAT
- Give the PAT a descriptive name and click Create
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use
With the Databricks connection configured and a PAT generated, Cursor can now connect to Databricks 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.
- Download the Cursor desktop application and complete the sign-up flow for your account
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From the top menu, click Settings to open the settings panel
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In the left navigation, open the Tools & MCP tab and click Add Custom MCP
- Cursor opens an mcp.json file in the editor
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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" } } } }
- Save the file
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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
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From the top bar, click Toggle AI Pane to open the chat window
- Test the connection by entering "List connections"
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You can also run queries like "Query Databricks data and list the high priority accounts"
Cursor is now fully integrated with the CData Connect AI MCP Server and can act on live Databricks 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!