Build Agents in Relevance AI with Access to Live Amazon S3 Data via CData Connect AI

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 Amazon S3 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 Amazon S3 connectivity in Connect AI, register Connect AI in Relevance AI, and build an agent that interacts with live Amazon S3 data.

Step 1: Configure Amazon S3 Connectivity for Relevance AI

Connectivity to Amazon S3 from Relevance AI is made possible through CData Connect AI's Remote MCP Server. To interact with Amazon S3 data from Relevance AI, we 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 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
👁 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, Relevance AI can now connect to Amazon S3 data through Connect AI.

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
👁 Creating a new agent in Relevance AI

3. Select Build from scratch and name the agent (eg; CData MCP Server)
👁 Building an agent from scratch

4. Inside the agent editor, select Advanced and then switch to the MCP Server tab
👁 Opening MCP Server settings

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)
👁 Connecting to CData Connect AI MCP Server in Relevance AI

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 Amazon S3 Data

1. Switch to the Run tab for your agent
2. Enter a task for example, "List the five most recent incidents from ServiceNow"
👁 Running the Relevance AI agent

3. The agent will query Connect AI via the MCP endpoint and display live results from Amazon S3 data
👁 Example query result from Connect AI

With the connection complete, Relevance AI agents can now issue queries, retrieve records, and perform AI-driven tasks over live Amazon S3 data through CData Connect AI MCP Server.

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