AWS Big Data Blog
Author: Lauren Mullennex
Accelerate your data and AI workflows by connecting to Amazon SageMaker Unified Studio from Visual Studio Code
In this post, we demonstrate how to connect your local VS Code to SageMaker Unified Studio so you can build complete end-to-end data and AI workflows while working in your preferred development environment.
Introducing enhanced AI assistance in Amazon SageMaker Unified Studio: Agentic chat, Amazon Q Developer CLI, and MCP integration
In this post, we will walk through how you can use the improved Amazon Q Developer chat and the new built-in Amazon Q Developer CLI in SageMaker Unified Studio for coding ETL tasks, to fix code errors, and generate ML development workflows. Both interfaces use MCP to read files, run commands, and interact with AWS services directly from the IDE. You can also configure additional MCP servers to extend Amazon Q Developer’s capabilities with custom tools and integrations specific to your workflow.