Build Agents in Relevance AI with Access to Live SingleStore 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 SingleStore 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 SingleStore 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 SingleStore connectivity in Connect AI, register the CData MCP Server in Relevance AI, and build an agent that interacts with live SingleStore data.

Step 1: Configure SingleStore Connectivity for Relevance AI

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

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

    The following connection properties are required in order to connect to data.

    • Server: The host name or IP of the server hosting the SingleStore database.
    • Port: The port of the server hosting the SingleStore database.
    • Database (Optional): The default database to connect to when connecting to the SingleStore Server. If this is not set, tables from all databases will be returned.

    Connect Using Standard Authentication

    To authenticate using standard authentication, set the following:

    • User: The user which will be used to authenticate with the SingleStore server.
    • Password: The password which will be used to authenticate with the SingleStore server.

    Connect Using Integrated Security

    As an alternative to providing the standard username and password, you can set IntegratedSecurity to True to authenticate trusted users to the server via Windows Authentication.

    Connect Using SSL Authentication

    You can leverage SSL authentication to connect to SingleStore data via a secure session. Configure the following connection properties to connect to data:

    • SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
    • SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
    • SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
    • SSLClientCertType: The certificate type of the client store.
    • SSLServerCert: The certificate to be accepted from the server.

    Connect Using SSH Authentication

    Using SSH, you can securely login to a remote machine. To access SingleStore data via SSH, configure the following connection properties:

    • SSHClientCert: Set this to the name of the certificate store for the client certificate.
    • SSHClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
    • SSHClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
    • SSHClientCertType: The certificate type of the client store.
    • SSHPassword: The password that you use to authenticate with the SSH server.
    • SSHPort: The port used for SSH operations.
    • SSHServer: The SSH authentication server you are trying to authenticate against.
    • SSHServerFingerPrint: The SSH Server fingerprint used for verification of the host you are connecting to.
    • SSHUser: Set this to the username that you use to authenticate with the SSH server.
  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 SingleStore connection configured and a PAT generated, Relevance AI can now connect to SingleStore 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 SingleStore 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 SingleStore data

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

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