Integrate Live SAS xpt Data in the Windsurf IDE via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Windsurf's Cascade agent to securely access and query live SAS xpt data from within the IDE.

Windsurf is an AI-native IDE built around Cascade, an autonomous coding agent that understands project context and executes multi-step tasks directly inside the editor. Cascade supports the Model Context Protocol (MCP), allowing the agent to discover and call external tools and data sources without leaving the development environment.

By integrating Windsurf with CData Connect AI through the built-in MCP server, the Cascade agent gains governed, real-time access to live SAS xpt data. This enables developers to list catalogs, inspect schemas, and query records from SAS xpt data within the IDE using natural language prompts.

This article explains how to configure SAS xpt connectivity in Connect AI, generate the required personal access token, configure the Connect AI MCP Server in Windsurf, and verify the integration by querying live SAS xpt data from the Cascade chat.

Step 1: Configure SAS xpt connectivity for Windsurf

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Select SAS xpt from the Add Connection panel
  3. Enter the necessary authentication properties to connect to SAS xpt.

    Connecting to Local SASXpt Files

    You can connect to local SASXpt file by setting the URI to a folder containing SASXpt files.

    Connecting to S3 data source

    You can connect to Amazon S3 source to read SASXpt files. Set the following properties to connect:

    • URI: Set this to the folder within your bucket that you would like to connect to.
    • AWSAccessKey: Set this to your AWS account access key.
    • AWSSecretKey: Set this to your AWS account secret key.
    • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

    Connecting to Azure Data Lake Storage Gen2

    You can connect to ADLS Gen2 to read SASXpt files. Set the following properties to connect:

    • URI: Set this to the name of the file system and the name of the folder which contacts your SASXpt files.
    • AzureAccount: Set this to the name of the Azure Data Lake storage account.
    • AzureAccessKey: Set this to our Azure DataLakeStore Gen 2 storage account access key.
    • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

  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 Windsurf. 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 SAS xpt connection configured and a PAT generated, Windsurf can now connect to SAS xpt data.

Step 2: Configure Connect AI MCP in Windsurf

Next, configure the Connect AI Remote MCP Server in Windsurf so that the Cascade agent can discover and call live data tools through Connect AI.

  1. Download and install the Windsurf IDE
  2. Open Windsurf, click your profile icon in the top right, and select Windsurf Settings
  3. Under the Cascade section, locate MCP Servers and click Open MCP Registry
  4. In the MCP Marketplace, click Add custom MCP in the top right
  5. This opens the mcp_config.json file. Paste the following JSON:
    {
        "mcpServers": {
            "cdata-mcp": {
                "serverUrl": "https://mcp.cloud.cdata.com/mcp",
                "headers": {
                    "Authorization": "Basic your_base64_encoded_email_PAT",
                    "Content-Type": "application/json"
                }
            }
        }
    }
    		

    Note: Windsurf will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

  6. Save the mcp_config.json file and return to the MCP Registry
  7. Under Installed, confirm that cdata-mcp is listed and marked as Enabled

With the MCP server registered and enabled, Windsurf is ready to query live SAS xpt data through Connect AI.

Step 3: Query live SAS xpt data from Windsurf

With the integration complete, use the Cascade chat panel in Windsurf to interact with live SAS xpt data through natural language prompts.

  1. On the top bar of Windsurf, switch from Editor to Agent to open a new Cascade chat
  2. At the bottom of the chat panel, confirm that the cdata-mcp server is listed and the toggle is enabled
  3. Start interacting with the agent by entering prompts like:
    • List all catalogs in my cdata-mcp connection
    • Show the available schemas and tables for SAS xpt
    • Query the top 5 records from a table in SAS xpt data
  4. The Cascade agent calls the Connect AI MCP Server and returns live results from SAS xpt data

At this point, your Windsurf IDE communicates with the Connect AI MCP Server and retrieves live SAS xpt data through remote MCP directly from the editor.

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