Build Voice Agents in ElevenLabs with access to Live Amazon S3 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 S3 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 S3 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 S3 data during conversations.

Step 1: Configure Amazon S3 connectivity for ElevenLabs

Connectivity to Amazon S3 from ElevenLabs is made possible through CData Connect AI's Remote MCP Server. To interact with Amazon S3 data from your voice agents, start by creating and configuring a Amazon S3 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 S3 from the Add Connection panel
👁 Selecting data source

3. Enter the necessary authentication properties to connect to Amazon S3.

   To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

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

   For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

   👁 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 S3 connection configured and a PAT generated, ElevenLabs can now connect to Amazon S3 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 S3 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 S3"
   • "Query recent records from Amazon S3 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 S3 data through the CData Connect AI Remote MCP Server, enabling real-time, data-driven voice interactions for your users.

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