Build Voice Agents in ElevenLabs with access to Live Amazon Athena Data

ElevenLabs is a leading AI audio platform that enables developers to build conversational voice agents capable of natural, human-like interactions. The ElevenLabs Conversational AI platform allows you to create voice-powered assistants that can reason through tasks, respond dynamically, and interact with external systems in real time.

By integrating ElevenLabs with CData Connect AI through the MCP (Model Context Protocol), your voice agents gain the ability to query, analyze, and act on live Amazon Athena data during conversations. This integration bridges ElevenLabs' conversational AI framework with the governed enterprise connectivity of CData Connect AI, ensuring all data access runs securely against authorized sources without manual data movement.

This article outlines the steps to configure Amazon Athena connectivity in Connect AI, generate the required authentication credentials, register the Connect AI MCP Server in ElevenLabs, and verify that your voice agent can successfully interact with live Amazon Athena data during conversations.

Getting Started

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Step 1: Configure Amazon Athena connectivity for ElevenLabs

Connectivity to Amazon Athena from ElevenLabs is made possible through CData Connect AI's Remote MCP Server. To interact with Amazon Athena data from your voice agents, 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 in Connect AI

2. Select Amazon Athena from the Add Connection panel
👁 Selecting 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 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 ElevenLabs. 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 (e.g., "ElevenLabs Voice Agent") 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 Amazon Athena connection configured and a PAT generated, ElevenLabs can now connect to Amazon Athena data through Connect AI.

Step 2: Add the Connect AI MCP Server in ElevenLabs

ElevenLabs supports connecting to external MCP servers that use SSE (Server-Sent Events) or HTTP streamable transport. The CData Connect AI Remote MCP Server is compatible with this integration.

1. Log into the ElevenLabs platform and navigate to your agent dashboard 👁 ElevenLabs agent dashboard
   
2. Go to Integrations and click + Add Integration to access the MCP server integrations section
3. Click on Custom MCP Server to add a new integration 👁 Adding a Custom MCP Server
   
4. Enter the following configuration:
   • Name: CData Connect AI
   • Description: Access live enterprise data from hundreds of sources
   • Server URL: https://mcp.cloud.cdata.com/sse
   • Secret Token: Leave empty (authentication is handled via headers)
   • HTTP Headers: Add a header with key Authorization and value Basic your_email:your_PAT
   👁 Configuring the CData Connect AI MCP server
   
5. Replace your_email:your_PAT with your Connect AI login email and the Personal Access Token you created earlier. For example: Basic [email protected]:ABC123...XYZ789
6. Click Save to test the connection and retrieve available tools from Connect AI
7. The CData Connect AI MCP server is now available to assign to your voice agents

Step 3: Configure your Voice Agent to use Connect AI

With the MCP server registered, you can now add it to your ElevenLabs voice agents to enable real-time data access during conversations.

1. Create a new agent or edit an existing agent in the ElevenLabs dashboard
2. In the agent configuration, navigate to the Tools section
3. Add the CData Connect AI MCP server you configured in Step 2 👁 Adding the MCP server to an agent
   
4. Configure the tool approval mode based on your requirements:
   • Always Ask: The agent will request permission before each data query (recommended for sensitive data)
   • Fine-Grained: Set approval requirements per tool/action
   • No Approval: The agent can query data autonomously
5. Save your agent configuration

Step 4: Interact with live data through your Voice Agent

Your ElevenLabs voice agent can now access and query live Amazon Athena data through the CData Connect AI MCP Server during conversations.

1. Start a conversation with your voice agent 👁 Starting a conversation with your voice agent
   
2. Ask your agent data-related questions such as:
   • "What connections are available?"
   • "Show me the schemas for Amazon Athena"
   • "Query recent records from Amazon Athena data"
   • "Summarize our latest Data"
3. The agent will use the Connect AI MCP tools to retrieve live data and respond conversationally 👁 Voice agent responding with data from Connect AI
   

Your ElevenLabs voice agent is now fully configured to access and query live Amazon Athena data through the CData Connect AI Remote MCP Server, enabling real-time, data-driven voice interactions for your users.

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