Integrate Live Adobe Analytics Data in the Windsurf IDE via CData Connect AI

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 Adobe Analytics data. This enables developers to list catalogs, inspect schemas, and query records from Adobe Analytics data within the IDE using natural language prompts.

This article explains how to configure Adobe Analytics 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 Adobe Analytics data from the Cascade chat.

Step 1: Configure Adobe Analytics connectivity for Windsurf

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

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a connection in Connect AI

2. Select Adobe Analytics from the Add Connection panel
👁 Selecting data source

3. Enter the necessary authentication properties to connect to Adobe Analytics.

   Adobe Analytics uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the "Getting Started" section of the help documentation for a guide.

   Retrieving GlobalCompanyId

   GlobalCompanyId is a required connection property. If you do not know your Global Company ID, you can find it in the request URL for the users/me endpoint on the Swagger UI. After logging into the Swagger UI Url, expand the users endpoint and then click the GET users/me button. Click the Try it out and Execute buttons. Note your Global Company ID shown in the Request URL immediately preceding the users/me endpoint.

   Retrieving Report Suite Id

   Report Suite ID (RSID) is also a required connection property. In the Adobe Analytics UI, navigate to Admin -> Report Suites and you will get a list of your report suites along with their identifiers next to the name.

   After setting the GlobalCompanyId, RSID and OAuth connection properties, you are ready to connect to Adobe Analytics.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based permissions
👁 Updating 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
👁 Creating a new PAT

4. Copy the token when displayed and store it securely. It will not be shown again

With the Adobe Analytics connection configured and a PAT generated, Windsurf can now connect to Adobe Analytics 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 👁 Opening Windsurf Settings from the profile menu
   
3. Under the Cascade section, locate MCP Servers and click Open MCP Registry 👁 Opening the MCP Registry from Cascade settings
   
4. In the MCP Marketplace, click Add custom MCP in the top right 👁 Adding a custom MCP server
   
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==

   👁 Pasting Connect AI MCP Server configuration
   
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 👁 Confirming cdata-mcp is installed and enabled
   

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

Step 3: Query live Adobe Analytics data from Windsurf

With the integration complete, use the Cascade chat panel in Windsurf to interact with live Adobe Analytics 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 👁 Enabling the cdata-mcp server in the Cascade chat
   
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 Adobe Analytics
   • Query the top 5 records from a table in Adobe Analytics data
4. The Cascade agent calls the Connect AI MCP Server and returns live results from Adobe Analytics data 👁 Querying live data from Cascade in Windsurf
   

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

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