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 developmentHow the LocalStack MCP Server turns manual cloud tasks into automated workflowsHow to set up and configure the server with your favorite AI editor (Cursor, VS Code, etc.)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.

We’re partnering with gdotv to simplify development with our Amazon Neptune cloud emulator component. You can now easily query, visualise and model your graph data either interactively or using the Gremlin querying language with G.V() - Gremlin IDE.With G.V(), you can considerably enhance your graph database development experience whilst gaining access to a powerful reporting and visualisation toolset for your production data. With LocalStack’s core cloud emulator, parity is ensured between a local Neptune instance and AWS’s own, meaning Gremlin queries in your development environment will behave identically on Amazon Neptune. In this video we demonstrate how to use G.V() with LocalStack Neptune.Read the announcement blog here: https://blog.localstack.cloud/2024-06-05-localstack-neptune-development-with-gv-gremlin-ide/

Debugging serverless functions has always been challenging, often requiring repeated invocations, extensive log tracing, and cloud deployments to diagnose an issue. The new Lambda Debug Mode in LocalStack changes this by allowing developers to debug AWS Lambda functions directly in their IDE, with breakpoints, variable inspection, and step-through execution, without leaving their local environment.In this presentation, Marco Edoardo Palma provides a hands-on demo of Lambda Debug Mode—from debugging standalone functions to handling multi-function workflows. Learn how this developer-first approach makes debugging serverless applications faster, smoother, and more intuitive.## Resources- Documentation: https://docs.localstack.cloud/user-guide/lambda-tools/debugging/#lambda-debug-mode-preview- Samples: https://github.com/localstack-samples/localstack-pro-samples/tree/master/lambda-debug-mode

Ever wish you could test your whole cloud app without touching the cloud? I’ll show you how to validate your serverless pipeline from start to finish, right on your laptop using LocalStack. Join our Slack community and start shipping with confidence.