What if your AI coding assistant could not only write infrastructure code, but also deploy it, test it, and fix issues automatically — all on your local machine? That's exactly what the LocalStack MCP Server makes possible. In this session, we'll introduce the LocalStack Model Context Protocol (MCP) Server, a new tool that lets AI agents manage your entire local cloud development lifecycle through a conversational interface. You'll learn what MCP is and why it's a game-changer for AI-assisted development, how the LocalStack MCP Server turns manual cloud tasks into automated workflows, how to set up and configure the server with your favorite AI editor (Cursor, VS Code, etc.), and real-world demos: deploying CDK apps, analyzing logs, running chaos tests, managing state with Cloud Pods, and more. Through hands-on examples, we'll walk through a complete workflow where an AI agent deploys a serverless application, verifies resources, troubleshoots issues, and tests resilience, all without leaving the conversation. If you've ever wished your AI assistant could do more than just generate code, this talk will show you what's possible when agents can actually manage your local cloud environment.

Connecting your applications to LocalStack has not always been easy. In this video, Simon from the LocalStack team discusses how we streamlined the LocalStack networking experience. We discussed the challenges of connecting your applications to LocalStack and how we're simplifying the LocalStack networking experience. Simon also discussed about configurations required for more complex networking setups, and some common networking scenarios, with example configuration for achieving connectivity.

LocalStack integrates with official AWS Software Development Kits (SDKs) so you can connect to LocalStack services using the same application code you use for AWS services. This lets you develop and test your applications locally without connecting to the cloud. In this video, we will talk about how you can connect to LocalStack emulated services using AWS SDKs.

LocalStack is ephemeral, so when you stop and restart it, all data is lost. You can use certain features to save the state & load it back when you restart LocalStack. This includes saving the local state for S3 buckets, DynamoDB tables, RDS databases and more. In this video, we explore three mechanisms that allow you to save state in LocalStack: persistence, state export and import, and Cloud Pods.