Integrating Boomi Agentstudio with Amazon Athena Data via CData Connect AI

Boomi Agentstudio is an enterprise platform for designing, orchestrating, and governing AI agents that automate tasks, enhance integration workflows, and support intelligent decision making across business processes. When you connect it with CData Connect AI, Boomi Agentstudio can securely access, query, and act on live enterprise data such as Amazon Athena through a standardized MCP tool interface.

CData Connect AI is a managed Model Context Protocol (MCP) platform that provides governed, real-time access to enterprise data systems. It exposes structured metadata, including catalogs, schemas, tables, and SQL querying across hundreds of data sources. With Connect AI, Boomi Agentstudio can incorporate live operational data directly into agent logic and workflow automation, eliminating the need for ETL pipelines, data replication, or custom integration code.

This article explains how to connect Boomi Agentstudio to a CData Connect AI MCP endpoint, configure access to your Amazon Athena or any other supported data source, and begin issuing real-time queries from within your agent-driven workflows.

Getting Started

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Prerequisites

• An account in Amazon Athena.
• An account in CData Connect AI
• An account of Boomi Agentstudio.

Step 1: Configure Amazon Athena connectivity for Boomi Agentstudio

For Boomi Agentstudio to access Amazon Athena, create a connection to Amazon Athena in CData Connect AI. This connection is then exposed to Boomi using the remote MCP server.

1. Log in to Connect AI click Sources, and then click + Add Connection 👁 Adding a Connection
   
2. From the available data sources, choose Amazon Athena 👁 Selecting a data source
   
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 to the access key Id. Set 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 to true and leave and 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 . 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 and of an IAM user to assume the role for. Roles may not be used when specifying the and of an AWS root user.

   Authenticating with MFA

   For users and roles that require Multi-factor Authentication, specify the and 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 (default 3600 seconds).

   Connecting to Amazon Athena

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

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

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Create & Test
5. Once authenticated, open the Permissions tab in the Amazon Athena connection and configure user-based permissions as required 👁 Updating permissions
   

Generate a Personal Access Token (PAT)

Boomi Agentstudio authenticates to Connect AI using an account email and a Personal Access Token (PAT). Creating separate PATs for each integration is recommended to maintain access control granularity.

1. In Connect AI, select the Gear icon in the top-right to open Settings
2. Under Access Tokens, select Create PAT
3. Provide a descriptive name for the token and select Create 👁 Creating a new PAT
   
4. Copy the token and store it securely. The PAT will only be visible during creation

With the Amazon Athena connection configured and a PAT generated, Boomi Agentstudio is ready to connect to Amazon Athena data via the CData Connect AI MCP server.

Step 2: Create a source using the CData Connect AI MCP endpoint

Start by creating a new MCP data source inside Boomi Agentstudio. This establishes a secure connection between Boomi and CData Connect AI, allowing agents to call MCP tools and work with live enterprise data.

To connect with Connect AI MCP as a source, follow the given process:

1. Log in to Boomi.
2. Open Services and select Agentstudio from the list. 👁 Select Agentstudio from Services list.
   
3. Go to the Sources tab and click Create a new source. 👁 Create a new source.
   
4. In the Agent Designer window, open the Sources tab and choose Model Context Protocol (MCP) as the source type. 👁 Select Model Context Protocol (MCP) as a source.
   
5. On the Create MCP Source screen, enter the following Configuration details:
   • Name: Provide a name for the source
   • Details: Add a short description for the source
   • Transport Type: Streamable HTTP
   • URL: https://mcp.cloud.cdata.com/mcp
   • Authentication: Basic Authentication
   • Username: Enter your Connect AI account username
   • Password: Enter your Connect AI PAT
6. Click Test Connection. 👁 Enter the configuration details for the source (Connect AI).
   
7. After you establish a successful connection, click Discover Tools. Boomi lists all MCP tools exposed by CData Connect AI, including queryData, getCatalogs, getSchemas, and getTables, along with the remaining tools, in the Tools tab.
8. Select all tools in the Discover and Select Tools section and click Continue. 👁 Discover and select the tools.
   
9. In the Review section, verify the details and click Save. 👁 Review the configuration and tools for the source.
   

Boomi adds the new source to the Sources tab.

👁 The new source is created.

Click the Tools tab to confirm that all tools from CData Connect AI appear in the list.

👁 All the tools from CData Connect AI appear in the list.

Step 3: Create a new agent

Create a new agent to interact with your Amazon Athena data. The agent acts as the interface between your prompts and the tools exposed by Connect AI, enabling it to process queries and return intelligent responses.

1. Go to the Agents tab and click Create New Agent. 👁 Create a new agent.
   
2. In the Agent Designer window, select Blank Template under the Agents tab. 👁 Select the Blank Template option from the Agents tab.
   
3. In the Profile section, enter the following details:
   • Basic Information: Specify the goal, agent name, and agent picture.
   • Agent Mode: Select either Conversational or Structured mode based on how you want the agent to respond to prompts, and configure the mode accordingly.
4. Click Save and Continue. 👁 Complete the Profile section.
   
5. In the Tasks section, define the actions your agent will perform:
   1. Click + Add New Task. 👁 Add a new task.
      
   2. In the Description tab, enter the task name and description. 👁 Add a name to the task along with a description.
      
   3. In the Instructions tab, click + Add New Instruction and describe how the agent should use the tool within this task. 👁 Add necessary instructions to the task.
      
   4. In the Tools tab, click + Add New Tool and select the tools exposed by Connect AI. Click Update Selected Tool, enable Requires Approval and Data Passthrough, save the task, and click Save and Continue. 👁 Select a tool from the list for the task.
      👁 The new task is added.
      

   Note: You can add up to 25 tools across all tasks.

6. In the Guardrails section, define the rules, restrictions, and filters to ensure your agent operates securely and ethically. Add a blocked message, denied topics, word filters, and custom regex patterns as required. Click Save and Continue. 👁 Add a guardrail.
   
7. In the Review section, verify all details and click Deploy to deploy the agent. 👁 Review the agent details and deploy the agent.
   

After you deploy the agent, use it to generate accurate and contextual responses to your prompts in the chat interface. 👁 The new agent is deployed.

Step 4: Prompt the Amazon Athena data using the agent

After you create and deploy your agent, interact with your Amazon Athena data using natural language prompts.

Follow these steps to prompt your Amazon Athena data:

1. Go to the Chat tab and select your agent from the dropdown list. 👁 Select your agent from the agent list in the chat.
   
2. Enter a prompt (for example, "How many tables are available in Amazon Athena?"). 👁 Enter a prompt.
   
3. The agent processes your prompt and returns the results. 👁 The agent processes your prompt and returns the desired result.
   

Get CData Connect AI

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today!