Integrate Dify with Live Amazon Athena Data via CData Connect AI

Anusha M B
Anusha M B
Technical Marketing Engineer
Use the CData Connect AI Remote MCP Server to enable Dify agents and workflows to securely access and query live Amazon Athena data.

Dify is an open source platform for building production-ready agentic workflows, chatbots, and other LLM applications. It includes built-in, two-way support for the model context protocol (MCP), allowing you to register remote MCP servers as tools in the platform to add external data sources and give your agents access to live data.

By integrating Dify with CData Connect AI through the built-in MCP Server, Dify gains governed, real-time access to live Amazon Athena data. You can list catalogs, explore schemas, and query records from Amazon Athena data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure Amazon Athena connectivity in Connect AI, generate the required personal access token, register the Connect AI MCP Server as a tool in Dify, add it to an agent application, and verify the integration by querying live Amazon Athena data from Dify.

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 Dify

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a connection in Connect AI
  3. Select Amazon Athena from the Add Connection panel
  4. Selecting data source
  5. 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.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Dify. 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. Creating a new PAT
  5. 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, Dify can now connect to Amazon Athena data through Connect AI.

Step 2: Register the Connect AI MCP Server in Dify

Next, register the Connect AI Remote MCP Server as a tool in Dify so your agents and workflows can discover and call live data tools through Connect AI.

  1. Log into Dify, or open your self-hosted Dify instance (version 1.6.0 or later, which includes built-in MCP support)
  2. Navigate to the Integrations page, select Tools and click MCP tab
  3. Navigate to MCP
  4. Click Add MCP Server (HTTP) and enter the following details:
    • Server URL: https://mcp.cloud.cdata.com/mcp
    • Name Icon: Give a descriptive name, for example, CData Connect AI
    • Server Identifier: A unique identifier, for example, cdata-connect-ai
    • Headers: Add an Authorization header with the value Basic your_base64_encoded_email_PAT

    Note: Dify will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic.

  5. Click Add & Authorize. Dify connects to the Connect AI MCP Server and lists the available tools Adding the Connect AI MCP Server in Dify

With the MCP server registered, the Connect AI tools are available to any agent application or workflow in your Dify workspace.

Step 3: Query live Amazon Athena data from Dify

With the integration complete, build an agent application in Dify and interact with live Amazon Athena data through natural language prompts.

  1. From the Dify Studio page, click Create from Blank and select Agent as the application type Viewing the Connect AI MCP tools in Dify
  2. In the agent configuration, click Add under the Tools section and select the Connect AI MCP tools registered in Step 2 Adding the Connect AI MCP tools to a Dify agent
  3. Select an LLM provider and model for the agent so it can interpret prompts and call MCP tools
  4. In the preview panel, type a prompt in the chat input, for example:
    • Use the cdata-connect-ai tools to list all available catalogs
    • Show the available schemas and tables for Amazon Athena
    • Query the top 5 records from a table in Amazon Athena
  5. The Dify agent calls the Connect AI MCP Server and returns live results from Amazon Athena data Querying live data from a Dify agent

At this point, Dify communicates with the Connect AI MCP Server and retrieves live Amazon Athena data through remote MCP tools directly from your agentic workflows.

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