Build Voice Agents in ElevenLabs with access to Live Sage X3 Cloud 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 Sage X3 Cloud 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 Sage X3 Cloud 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 Sage X3 Cloud data during conversations.

Step 1: Configure Sage X3 Cloud connectivity for ElevenLabs

Connectivity to Sage X3 Cloud from ElevenLabs is made possible through CData Connect AI's Remote MCP Server. To interact with Sage X3 Cloud data from your voice agents, start by creating and configuring a Sage X3 Cloud connection in CData Connect AI.

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

2. Select Sage X3 Cloud from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage X3 Cloud.

   Sage X3 Cloud uses the OAuth 2.0 Client Credentials flow, and an X-API-Key is also required for API access. Set AuthScheme to OAuth and specify the following connection properties:

   • URL: The base URL of your Sage X3 Cloud instance.
   • OAuthAccessTokenUrl: The OAuth token endpoint (e.g., https://your-auth-domain/oauth/token).
   • OAuthClientId: Your OAuth application client ID.
   • OAuthClientSecret: Your OAuth application client secret.
   • Audience: The API audience value for the token request.
   • XAPIKey: The X-API-Key provided by your Sage X3 Cloud administrator.
   • Folder: The Sage X3 folder name (e.g., SEED). This folder is used as the default schema.
   • Folders (optional): A comma-separated list of Sage X3 folders (e.g., SEED,PERF). Each folder is exposed as a separate schema, so you can query across folders with the Schema.Table syntax.

   The driver obtains an access token with the Client Credentials flow and sends it with the X-API-Key on every API request. With InitiateOAuth set to GETANDREFRESH (the default), the driver acquires and refreshes the token automatically.

   
4. Click Save & Test
5. Navigate to the Permissions tab and update user-based 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

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

With the Sage X3 Cloud connection configured and a PAT generated, ElevenLabs can now connect to Sage X3 Cloud 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
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
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
   
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
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 Sage X3 Cloud data through the CData Connect AI MCP Server during conversations.

1. Start a conversation with your voice agent
2. Ask your agent data-related questions such as:
   • "What connections are available?"
   • "Show me the schemas for Sage X3 Cloud"
   • "Query recent records from Sage X3 Cloud data"
   • "Summarize our latest Data"
3. The agent will use the Connect AI MCP tools to retrieve live data and respond conversationally

Your ElevenLabs voice agent is now fully configured to access and query live Sage X3 Cloud data through the CData Connect AI Remote MCP Server, enabling real-time, data-driven voice interactions for your users.

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