Integrate Open WebUI with Live Amazon Athena Data via CData Connect AI

Open WebUI is an open-source, self-hosted AI chat platform that brings together hosted LLM APIs and locally served models under a single, customizable interface. It supports the Model Context Protocol (MCP) through its tool server framework, allowing you to configure external tools and data sources so that chats can reach beyond the model's training data and interact with live systems.

By integrating Open WebUI with CData Connect AI through the built-in MCP Server, Open WebUI gains governed, real-time access to live Amazon Athena data. This enables users to 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, install Open WebUI, register the Connect AI MCP Server, configure an LLM provider, and verify the integration by querying live Amazon Athena data from the Open WebUI chat interface.

Getting Started

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Step 1: Configure Amazon Athena connectivity for Open WebUI

Connectivity to Amazon Athena from Open WebUI is made possible through Connect AI's Remote MCP Server. To interact with Amazon Athena data from Open WebUI, 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. 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 Open WebUI. 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, Open WebUI can now connect to Amazon Athena data through Connect AI.

Step 2: Install Open WebUI and configure Connect AI MCP

Next, install Open WebUI locally and configure the Connect AI Remote MCP Server as a tool server so that the chat interface can discover and call live data tools through Connect AI.

1. Install Open WebUI by following the official Quick Start guide
2. Once the installation is complete, start Open WebUI and open it in your browser to access the chat interface
3. Click your profile icon in the top right and select Admin Panel
4. In the top navigation bar of the Admin Panel, click Settings
5. Select Integrations from the left menu, then click the icon next to Manage Tool Servers to add a new connection
6. In the Add Connection panel, configure the server with the following values:
   • Type: MCP Streamable HTTP
   • Name: CData MCP, or any name of your choice
   • ID: cdata-mcp
   • URL: https://mcp.cloud.cdata.com/mcp
   • Auth: None
7. Expand the Advanced section and paste the following JSON into the Headers field:

   {
       "Authorization": "Basic your_base64_encoded_email_PAT",
       "Content-Type": "application/json"
   }
   		

   Note: Open WebUI 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. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

   
8. Click Save to register the tool server

Enable the MCP server and configure an LLM provider

Open WebUI requires at least one LLM provider to power the chat. Enable the MCP server from the chat input and configure an API key for your preferred provider so the model can interpret prompts and call MCP tools through Connect AI.

1. Return to the chat interface, click the Integrations icon at the bottom of the chat input, select Tools, and toggle CData MCP on to expose the tools to the chat
2. At the top of the chat, click the model selector and choose your preferred LLM provider and model. Add your provider API key when prompted so the model can be used in the chat

With the MCP server and an LLM provider configured, Open WebUI is ready to query live Amazon Athena data through Connect AI.

Step 3: Query live Amazon Athena data from Open WebUI

With the integration complete, use the Open WebUI chat input to interact with live Amazon Athena data through natural language prompts handled by the configured LLM.

1. With the CData MCP server enabled and a model selected, type a prompt in the chat input, for example:
   • List all catalogs in my cdata mcp
   • Show the available schemas and tables for Amazon Athena
   • Query the top 5 records from a table in Amazon Athena data
2. Open WebUI calls the Connect AI MCP Server and returns live results from Amazon Athena data

At this point, your Open WebUI instance communicates with the Connect AI MCP Server and retrieves live Amazon Athena data through remote MCP tools directly from the chat interface.

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