Build Agents in Relevance AI with Access to Live SQL Server Data via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Relevance AI to securely access and act on SQL Server data within intelligent agent workflows.

Relevance AI is an AI automation and agent-building platform that enables organizations to create autonomous workflows powered by natural language reasoning. Users can visually design agents that interact with APIs, databases, and third-party systems to complete everyday business tasks or data operations.

By integrating Relevance AI with CData Connect AI through the built-in MCP (Model Context Protocol) Server, your agents can query, summarize, and act on live SQL Server data in real time. This connection bridges Relevance AI intelligent workflow engine with the governed enterprise connectivity of CData Connect AI ensuring every query runs securely against authorized sources without manual data export.

This article outlines the steps to configure SQL Server connectivity in Connect AI, register the CData MCP Server in Relevance AI, and build an agent that interacts with live SQL Server data.

Step 1: Configure SQL Server Connectivity for Relevance AI

Connectivity to SQL Server from Relevance AI is made possible through CData Connect AI's Remote MCP Server. To interact with SQL Server data from Relevance AI, we start by creating and configuring a SQL Server connection in CData Connect AI.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Select SQL Server from the Add Connection panel
  3. Enter the necessary authentication properties to connect to SQL Server.

    Connecting to Microsoft SQL Server

    Connect to Microsoft SQL Server using the following properties:

    • Server: The name of the server running SQL Server.
    • User: The username provided for authentication with SQL Server.
    • Password: The password associated with the authenticating user.
    • Database: The name of the SQL Server database.

    Connecting to Azure SQL Server and Azure Data Warehouse

    You can authenticate to Azure SQL Server or Azure Data Warehouse by setting the following connection properties:

    • Server: The server running Azure. You can find this by logging into the Azure portal and navigating to "SQL databases" (or "SQL data warehouses") -> "Select your database" -> "Overview" -> "Server name."
    • User: The name of the user authenticating to Azure.
    • Password: The password associated with the authenticating user.
    • Database: The name of the database, as seen in the Azure portal on the SQL databases (or SQL warehouses) page.

    SSH Connectivity for SQL Server

    You can use SSH (Secure Shell) to authenticate with SQL Server, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).

    SSH Connections to SQL Server in Password Auth Mode

    To connect to SQL Server via SSH in Password Auth mode, set the following connection properties:

    • User: SQL Server User name
    • Password: SQL Server Password
    • Database: SQL Server database name
    • Server: SQL Server Server name
    • Port: SQL Server port number like 3306
    • UserSSH: "true"
    • SSHAuthMode: "Password"
    • SSHPort: SSH Port number
    • SSHServer: SSH Server name
    • SSHUser: SSH User name
    • SSHPassword: SSH Password

    SSH Connections to SQL Server in Public Key Auth Mode

    To connect to SQL Server via SSH in Password Auth mode, set the following connection properties:

    • User: SQL Server User name
    • Password: SQL Server Password
    • Database: SQL Server database name
    • Server: SQL Server Server name
    • Port: SQL Server port number like 3306
    • UserSSH: "true"
    • SSHAuthMode: "Public_Key"
    • SSHPort: SSH Port number
    • SSHServer: SSH Server name
    • SSHUser: SSH User name
    • SSHClientCret: the path for the public key certificate file
  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 Relevance AI. 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 and click Create
  4. Copy the token when displayed and store it securely. It will not be shown again

With the SQL Server connection configured and a PAT generated, Relevance AI can now connect to SQL Server data through the CData MCP Server.

Step 2: Configure Connectivity in Relevance AI

The CData Connect AI MCP endpoint and authorization details are registered within Relevance AI so that agents can call live data from Connect AI.

  1. Sign in to Relevance AI and create an account if you do not already have one
  2. From the sidebar, navigate to Agents and then click on New Agent
  3. Select Build from scratch and name the agent (eg; CData MCP Server)
  4. Inside the agent editor, select Advanced and then switch to the MCP Server tab
  5. Click + Add Remote MCP Tools
  6. In the dialog that appears, fill out the fields as follows:
    • URL: https://mcp.cloud.cdata.com/mcp
    • Label: Any custom label (eg; cdata_mcp_server)
    • Authentication: Select Custom headers
    • Add header key:value pair. Combine your email and PAT as email:PAT and encode that string in Base64 and then prefix with the word Basic
      • Key: Authorization
      • Value: Basic base64(email:PAT)

Click Connect to establish the connection. Relevance AI will verify your credentials and register the CData Connect AI MCP Server for use in agents.

Step 3: Build and Run a Relevance AI Agent with Live SQL Server Data

  1. Switch to the Run tab for your agent
  2. Enter a task for example, "List the five most recent incidents from ServiceNow"
  3. The agent will query Connect AI via the MCP endpoint and display live results from SQL Server data

With the connection complete, Relevance AI agents can now issue queries, retrieve records, and perform AI-driven tasks over live SQL Server data through CData Connect AI MCP Server.

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