Use Manus AI to Talk to Your Amazon Athena Data via CData Connect AI

Manus AI is an autonomous AI agent platform that helps users accomplish complex tasks through natural language from browsing the web to executing code and interacting with external services. When combined with CData Connect AI remote MCP, users can leverage Manus AI to interact with their Amazon Athena data in real-time, without any data replication.

This article explains how to connect to Amazon Athena using the CData Connect AI MCP Server and configure Manus AI to conversationally explore (or Vibe Query) their Amazon Athena data. With Connect AI, users can build AI agents with access to live Amazon Athena data, plus hundreds of other sources.

Getting Started

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Step 1: Configure Amazon Athena connectivity for Manus AI

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

1. Log into Connect AI, click Connections and click Add Connection 👁 Adding a Connection
   
2. Select "Amazon Athena" from the Add Connection panel 👁 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)
   Click Save & Test
4. Navigate to the Permissions tab in the Add Amazon Athena Connection page and update the 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 Manus AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to Amazon Athena data from Manus AI.

Step 2: Get started with Manus AI

Navigate to Manus and sign in to your Manus AI account. Once logged in, you are ready to configure the CData Connect AI MCP Server as a custom connector.

Step 3: Add the CData Connect AI MCP Server as a connector

Manus AI supports connecting to external MCP servers via its Connectors settings. There are two methods to add the CData Connect AI MCP Server: Import by JSON or Direct Configuration. Both methods are explained below.

1. In Manus AI, click on the profile icon and navigate to Settings 👁 Navigating to Manus AI settings
   
2. Go to the Connectors section and click Add Connectors 👁 Navigating to Custom MCP connectors
   
3. Locate Custom MCP 👁 Click Custom MCP
   
4. Click Add custom MCP to select the configuration options 👁 Add custom MCP
   

Option A: Import by JSON

Use this method to quickly configure the MCP Server by pasting a JSON configuration snippet.

1. Select Import by JSON from the connector setup options.
2. Paste the following JSON into the configuration field, replacing the placeholder values with your Connect AI credentials:

   {
    "mcpServers": {
    "cdata-connect-ai": {
    "transport": "sse",
    "url": "https://mcp.cloud.cdata.com/mcp",
    "headers": {
    "Authorization": "Basic USER_NAME:YOUR_CONNECTAI_PAT;"
    }
    }
    }
   }
    

   Replace url with the Connect AI MCP URL, USER_NAME with your Connect AI email address, and YOUR_CONNECTAI_PAT with the Personal Access Token created in Step 1. 👁 Importing MCP configuration via JSON in Manus AI
   
3. Click Import to apply the configuration.

Option B: Direct Configuration

Use this method to manually enter the MCP Server connection properties through the Manus AI interface.

1. Select Direct Configuration from the connector setup options.
2. Fill in the following fields:
   • Server Name: CData Connect AI
   • Transport Type: HTTP
   • Server URL: https://mcp.cloud.cdata.com/mcp
   • Custom Headers: Add a header with the name Authorization and the value Basic Base64Encoded(username:pat), replacing the placeholder with your Base64-encoded Connect AI email and PAT combination.
   👁 Configuring the CData Connect AI MCP Server directly in Manus AI
   
3. Optionally, enter a Note to provide Manus AI with instructions on how and when to use this MCP connector.
4. Click Save to establish the connection to the CData Connect AI MCP Server. Once saved, the connector will appear as active in your Connectors list.

Step 4: Query your Amazon Athena data using natural language

With the CData Connect AI MCP configured in Manus AI, users can now interact with their Amazon Athena data using natural language in any new Manus AI chat session.

1. Open a new chat in Manus AI.
2. Start asking questions about the Amazon Athena data. For example:
   • Show me all customers from the last 30 days
   • What are my top performing products?
   • Analyze sales trends for Q4
   • List all active projects with their current status
3. Manus AI will use the CData Connect AI MCP Server to query your Amazon Athena data in real-time and provide responses based on live data. 👁 Chatting with live data in Manus AI
   

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!