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

About Amazon Athena Data Integration

CData provides the easiest way to access and integrate live data from Amazon Athena. Customers use CData connectivity to:

  • Authenticate securely using a variety of methods, including IAM credentials, access keys, and Instance Profiles, catering to diverse security needs and simplifying the authentication process.
  • Streamline their setup and quickly resolve issue with detailed error messaging.
  • Enhance performance and minimize strain on client resources with server-side query execution.

Users frequently integrate Athena with analytics tools like Tableau, Power BI, and Excel for in-depth analytics from their preferred tools.

To learn more about unique Amazon Athena use cases with CData, check out our blog post: https://www.cdata.com/blog/amazon-athena-use-cases.


Getting Started


Step 1: Configure Amazon Athena Connectivity for Relevance AI

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

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

    Authenticating to Amazon Athena

    To authorize Amazon Athena 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: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.

    Obtaining the Access Key

    To obtain the credentials for an IAM user, follow the steps below:

    1. Sign into the IAM console.
    2. In the navigation pane, select Users.
    3. To create or manage the access keys for a user, select the user and then select the Security Credentials tab.

    To obtain the credentials for your AWS root account, follow the steps below:

    1. Sign into the AWS Management console with the credentials for your root account.
    2. Select your account name or number and select My Security Credentials in the menu that is displayed.
    3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

    Authenticating from an EC2 Instance

    If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set UseEC2Roles to true and leave AccessKey and SecretKey empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.

    Authenticating as an AWS Role

    In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the RoleARN. This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the AccessKey and SecretKey of an IAM user to assume the role for. Roles may not be used when specifying the AccessKey and SecretKey of an AWS root user.

    Authenticating with MFA

    For users and roles that require Multi-factor Authentication, specify the MFASerialNumber and MFAToken connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the TemporaryTokenDuration (default 3600 seconds).

    Connecting to Amazon Athena

    In addition to the AccessKey and SecretKey properties, specify Database, S3StagingDirectory and Region. Set Region to the region where your Amazon Athena data is hosted. Set S3StagingDirectory to a folder in S3 where you would like to store the results of queries.

    If Database is not set in the connection, the data provider connects to the default database set in Amazon Athena.

  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 Amazon Athena connection configured and a PAT generated, Relevance AI can now connect to Amazon Athena 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 Amazon Athena 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 Amazon Athena data

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

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