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⇱ How to Query Live Amazon S3 Data in Perplexity MacOS Desktop


How to Query Live Amazon S3 Data in Perplexity MacOS Desktop

πŸ‘ Yazhini G
Yazhini G
Technical Marketing Engineer
Connect to and query live Amazon S3 Data in Perplexity Desktop using CData Code Assist MCP.

Perplexity is an AI-powered research and answer engine that allows users to combine web search, structured data, and connected tools through a unified conversational interface. With Perplexity Desktop for macOS, users can bring local tools and data sources directly into their workflow using MCP, enabling fast, context-aware insights powered by live data.

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and enterprise data sources. Using MCP Servers, AI clients such as Perplexity Desktop can securely interact with applications and data, performing actions, retrieving live information, and enabling natural language access to data.

CData Code Assist MCP provides schema-aware context to AI tools β€” whether you're using it for AI-assisted code generation in IDEs like Cursor, or for querying live data through chat interfaces like Perplexity Desktop.

In this article, we guide you through installing CData Code Assist MCP for Amazon S3, configuring the connection to Amazon S3, and interacting with your live Amazon S3 data from Perplexity Desktop.

Step 1: Download and install CData Code Assist MCP for Amazon S3

  1. To begin, download CData Code Assist MCP for Amazon S3 πŸ‘ Downloading the CData Code Assist MCP installer
  2. Find and double-click the installer to begin the installation
  3. Drag the Code Assist MCP app into the Applications folder πŸ‘ Completing the Code Assist MCP installation

When the installation is complete, you are ready to configure Code Assist MCP by connecting to Amazon S3.

NOTE: Since you downloaded the application from the internet and not the Apple App Store, you may see a warning that the application was not opened because Apple could not verify its security. You may continue with the installation.

Installing a trusted, unverified App

CData's solutions are trusted across the globe by some of the largest software vendors in the world. That said, if you have any concerns about continuing, please consult with your IT and/or security team.

  1. In the warning message that pops up, click "Done"
  2. Open "System Settings" on your machine and navigate to the "Privacy & Security" page
  3. πŸ‘ Dismissing the notification
  4. Scroll down to the "Security" section and click "Open Anyway" πŸ‘ Installing a trusted, unverified App
  5. Authorize the installation (passkey or password) πŸ‘ Authorizing the installation

Step 2: Configure the Connection to Amazon S3

  1. After installation, you can open CData Code Assist MCP for Amazon S3 from the Applications folder on your mac πŸ‘ The Code Assist MCP configuration wizard
  2. Click the dropdown menu in MCP Configuration > Configuration Name and select "new configuration" πŸ‘ Creating a new configuration
  3. Name the configuration (e.g. "cdata_amazons3") and click "OK" πŸ‘ Naming the configuration
  4. Enter the appropriate connection properties in the configuration wizard.

    To authorize Amazon S3 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: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

    For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

    πŸ‘ Configuring the Server connection.
  5. Click "Connect" to authenticate with Amazon S3.
  6. Click "Save Configuration" to save the configuration πŸ‘ Saving the Code Assist MCP configuration

With Code Assist MCP configured, you are ready to connect it to Perplexity Desktop.

Step 3: Connect Code Assist MCP to Perplexity Desktop

  1. Download the Perplexity Desktop application for macOS and sign in with your Pro or Premium account
  2. Open Settings > Connectors. If the Perplexity Helper App is not installed, you will be prompted to download it. Install the Helper App, then restart Perplexity Desktop πŸ‘ Downloading Perplexity Helper App
  3. After restarting, return to Settings > Connectors and click Add Connector
  4. Select the Simple tab and assign a name for the connector (e.g., "CData Amazon S3"). In the Command box, enter the absolute path to the Code Assist MCP executable.

    For example:

    	/Applications/CData Code Assist MCP for Amazon S3.app/Contents/Payload/jre/Contents/Home/bin/java \
    	-jar /Applications/CData Code Assist MCP for Amazon S3.app/Contents/Payload/lib/cdata.mcp.amazons3.jar \
    	cdata_amazons3
    
    πŸ‘ Providing the MCP server command
  5. Click Save. Code Assist MCP should now appear in the connector list with a "Running" status πŸ‘ Connector successfully running

Step 4: Query Your Live Amazon S3 data in Perplexity Desktop

  1. Open a new chat in Perplexity Desktop. Click the Sources toggle and enable Code Assist MCP πŸ‘ Selecting Code Assist MCP as a source
  2. Start asking questions about your Amazon S3 data. For example:

    "List all the tables available in my Amazon S3 data connection."

    πŸ‘ Querying live data through MCP

Build with Code Assist MCP. Deploy with CData Drivers.

Download Code Assist MCP for free and give your AI tools schema-aware access to live Amazon S3 data during development. When you're ready to move to production, CData Amazon S3 Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.

Ready to get started?

Download a free Amazon S3 Code Assist MCP to get started:

 Download Now

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Amazon S3 Code Assist MCP

The CData Code Assist MCP for Amazon S3 provides schema-aware context for AI-assisted code generation with live Amazon S3 data.