Connecting GenSpark with Amazon Athena 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.

Getting Started

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Prerequisites

Before starting, ensure you have:

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

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 Amazon Athena connectivity for GenSpark

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

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

2. Select "Amazon Athena" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Amazon Athena.

   Authenticating to Amazon Athena

   To authorize Amazon Athena requests, provide the credentials for an administrator account or for an IAM user with custom permissions: Set to the access key Id. Set to the secret access key.

   Note: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.

   Obtaining the Access Key

   To obtain the credentials for an IAM user, follow the steps below:

   1. Sign into the IAM console.
   2. In the navigation pane, select Users.
   3. To create or manage the access keys for a user, select the user and then select the Security Credentials tab.

   To obtain the credentials for your AWS root account, follow the steps below:

   1. Sign into the AWS Management console with the credentials for your root account.
   2. Select your account name or number and select My Security Credentials in the menu that is displayed.
   3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

   Authenticating from an EC2 Instance

   If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set to true and leave and empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.

   Authenticating as an AWS Role

   In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the . This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the and of an IAM user to assume the role for. Roles may not be used when specifying the and of an AWS root user.

   Authenticating with MFA

   For users and roles that require Multi-factor Authentication, specify the and connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the (default 3600 seconds).

   Connecting to Amazon Athena

   In addition to the and properties, specify , and . Set to the region where your Amazon Athena data is hosted. Set to a folder in S3 where you would like to store the results of queries.

   If is not set in the connection, the data provider connects to the default database set in Amazon Athena.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Amazon Athena Connection page and update the 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 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. 👁 Creating a new PAT
   
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 Amazon Athena data from GenSpark.

Step 2: Configure MCP Server in GenSpark

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

3. Select Add new MCP server
👁 Add new MCP Tool


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 👁 Server Configuration
   

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 hundreds of external systems.