Build Voice Agents in ElevenLabs with access to Live Sage 300 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 300 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 300 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 300 data during conversations.
Step 1: Configure Sage 300 connectivity for ElevenLabs
Connectivity to Sage 300 from ElevenLabs is made possible through CData Connect AI's Remote MCP Server. To interact with Sage 300 data from your voice agents, start by creating and configuring a Sage 300 connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select Sage 300 from the Add Connection panel
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Enter the necessary authentication properties to connect to Sage 300.
Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.
- Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the
option under Security Groups (per each module required). - Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
- Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.
Authenticate to Sage 300 using Basic authentication.
Connect Using Basic Authentication
You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.
- Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
- User: Set this to the username of your account.
- Password: Set this to the password of your account.
- Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the
- Click Save & Test
- 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.
- Click the gear icon () at the top right of the Connect AI app to open Settings
- On the Settings page, go to the Access Tokens section and click Create PAT
- Give the PAT a descriptive name (e.g., "ElevenLabs Voice Agent") and click Create
- Copy the token when displayed and store it securely. It will not be shown again
With the Sage 300 connection configured and a PAT generated, ElevenLabs can now connect to Sage 300 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.
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Log into the ElevenLabs platform and navigate to your agent dashboard
- Go to Integrations and click + Add Integration to access the MCP server integrations section
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Click on Custom MCP Server to add a new integration
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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
- 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
- Click Save to test the connection and retrieve available tools from Connect AI
- 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.
- Create a new agent or edit an existing agent in the ElevenLabs dashboard
- In the agent configuration, navigate to the Tools section
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Add the CData Connect AI MCP server you configured in Step 2
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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
- 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 300 data through the CData Connect AI MCP Server during conversations.
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Start a conversation with your voice agent
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Ask your agent data-related questions such as:
- "What connections are available?"
- "Show me the schemas for Sage 300"
- "Query recent records from Sage 300 data"
- "Summarize our latest Data"
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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 300 data through the CData Connect AI Remote MCP Server, enabling real-time, data-driven voice interactions for your users.
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