Connecting GenSpark with Confluence Data via CData Connect AI MCP Server

GenSpark is built for developers and enterprise teams who want to create intelligent, conversational AI experiences powered by real-time data. It's flexible tooling and agentic capabilities make it easy to integrate LLMs, automate complex workflows, and build interactive applications that adapt to user intent. However, when these AI interactions require data beyond local context or predefined APIs, many implementations fall back on custom middleware, manual integrations, or scheduled ETL pipelines to sync information into local stores. This introduces unnecessary complexity, increases maintenance overhead, slows response times, and limits the real-time intelligence your GenSpark agents can provide.

CData Connect AI eliminates these barriers by delivering live, secure connectivity to more than 300 enterprise applications, databases, ERPs, and analytics platforms. Through CData Connect AI remote Model Context Protocol (MCP) Server, GenSpark agents can query, read, and act on real-time enterprise data without replication or custom integration code. The result is grounded, accurate responses, faster reasoning, and automated, cross-system decision-making all with stronger governance and fewer moving parts.

This guide outlines the steps required to configure CData Connect AI MCP connectivity, register the MCP Server in GenSpark, and enable your GenSpark agents to work seamlessly with live enterprise data in real time.

Prerequisites

Before starting, ensure you have:

1. A CData Connect AI account
2. Access to GenSpark
3. Access to Confluence

Credentials checklist

Ensure you have these credentials ready for the connection:

1. USERNAME: Your CData email login
2. PAT: Connect AI, go to Settings and click on Access Tokens (copy once)
3. MCP_BASE_URL: https://mcp.cloud.cdata.com/mcp

Step 1: Configure Confluence connectivity for GenSpark

Connectivity to Confluence from GenSpark is made possible through CData Connect AI Remote MCP. To interact with Confluence data from GenSpark, we start by creating and configuring a Confluence connection in CData Connect AI.

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

2. Select "Confluence" from the Add Connection panel

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

   Obtaining an API Token

   An API token is necessary for account authentication. To generate one, login to your Atlassian account and navigate to API tokens > Create API token. The generated token will be displayed.

   Connect Using a Confluence Cloud Account

   To connect to a Cloud account, provide the following (Note: Password has been deprecated for connecting to a Cloud Account and is now used only to connect to a Server Instance.):

   • User: The user which will be used to authenticate with the Confluence server.
   • APIToken: The API Token associated with the currently authenticated user.
   • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.

   Connect Using a Confluence Server Instance

   To connect to a Server instance, provide the following:

   • User: The user which will be used to authenticate with the Confluence instance.
   • Password: The password which will be used to authenticate with the Confluence server.
   • Url: The URL associated with your JIRA endpoint. For example, https://yoursitename.atlassian.net.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Confluence Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from GenSpark. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a 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 connection configured and a PAT generated, we are ready to connect to Confluence data from GenSpark.

Step 2: Configure MCP Server in GenSpark

1. Log in to GenSpark
2. Below the chat interface, click the Tools icon

3. Select Add new MCP server


4. Fill in the server configuration:

   NOTE: Use Basic authentication, where you combine your Connect AI email address (e.g. [email protected]) with the PAT you generated earlier (e.g. AbC123...xYz890) with a colon (:) in the Authorization header.

   
   

   Field	Value
   Name	CData MCP Server (or any name you prefer)
   Server Type	SteamableHttp
   Server URL	https://mcp.cloud.cdata.com/mcp
   Request Header	{"Authorization": "Basic [email protected]:AbC123...xYz890"}

5. Click Add Server

Once added, GenSpark will automatically load all MCP tools exposed through your Connect AI workspace.

Step 3: Query data in GenSpark

In GenSpark chat interface enter any sample prompt:

List the tools present in CData Connect AI MCP Server.

Build real-time, data-aware agents with GenSpark and CData

GenSpark and CData Connect AI together enable intelligent, AI-driven workflows where agents can securely access live enterprise data and operate with real-time awareness without ETL pipelines, data sync jobs, or custom integration logic. This streamlined approach delivers stronger governance, lower operational overhead, and faster, more grounded responses from your AI tools.

Start your free trial today to see how CData can empower GenSpark with live, secure access to 300+ external systems.