Today, AWS announced cross-account and cross-role access for the AWS Model Context Protocol (MCP) Server, part of the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/. This feature allows developers using AI coding agents like Kiro, Claude Code, or Codex to work across multiple AWS accounts and AWS Identity and Access Management (IAM) roles within a single session, with no restarts required. Previously, switching profiles required stopping the AI coding session, updating local AWS credentials, and restarting the MCP server for every account change. Now, AI agents using the AWS MCP Server can specify a profile on each command, allowing users to switch between accounts and roles seamlessly. Cross-account access helps developers move faster across multi-account environments. For example, a DevOps engineer can query CloudWatch logs across production and staging accounts to diagnose a performance issue, or an application developer can update a Lambda configuration in one account and adjust an S3 bucket policy in another, all within the same conversation. Each request specifies which profile to use, so there is no risk of commands reaching the wrong account. To get started, see https://docs.aws.amazon.com/agent-toolkit/latest/userguide/multi-account-access.html in the Agent Toolkit for AWS user guide. The AWS MCP Server is available in the US East (N. Virginia) and Europe (Frankfurt) Regions.

Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Model providers and AI researchers building agents that operate on AWS infrastructure need an objective, reproducible way to measure performance and diagnose failures. aws-bench provides a public suite of test cases derived from analysis of real AWS usage, including investigation, troubleshooting, and infrastructure creation tasks. Each test case pairs a natural-language query with a defined cloud resource state and a ground-truth answer, so you can score any agent or model on a consistent, verifiable basis. Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress. The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state. aws-bench is available now on https://github.com/aws-bench/aws-bench. To get started, follow the setup instructions on the README. 

Today, AWS Model Context Protocol Server (AWS MCP Server) added a serverless capability so that coding agents such as Claude Code and Kiro can efficiently diagnose issues with your Lambda functions. The serverless capability helps you troubleshoot your running Lambda functions and their connected resources. The AWS MCP Server, available through the Agent Toolkit for AWS or as a standalone installation, is a managed service that gives AI coding agents secure access to AWS services. With the new AWS MCP Sever serverless capability, your coding agent inspects your Lambda function and its connected resources across Amazon API Gateway, Amazon EventBridge, Amazon S3, Amazon DynamoDB, Amazon SNS, Amazon SQS, and AWS Step Functions. The agent can correlate error signals against a 7-day baseline to pinpoint what changed, surface recurring errors to identify trends, retrieve the deployed configuration of your function and connected resources, provide a timeline of recent changes to track what happened, and analyze service latency across connected resources. As the agent gets comprehensive data in a single call, it consumes fewer tokens compared to orchestrating multiple API calls. To get started, configure the Agent toolkit for AWS by running ‘aws configure agent-toolkit’ from the AWS CLI, or enable the AWS MCP Server directly. The AWS MCP Server can access services in all commercial AWS Regions, while the AWS MCP Server itself runs in the US East (N. Virginia) and Europe (Frankfurt) Regions. The serverless diagnostic capabilities in the AWS MCP Server are available at no additional cost. To learn more, see the user guide.

Today, AWS is launching the Agent Toolkit for AWS, a production-ready suite of tools and guidance that helps AI coding agents build on AWS with fewer errors, lower token costs, and enterprise-grade security controls. The Agent Toolkit for AWS is the successor to the MCP servers, plugins, and skills available on https://github.com/awslabs. Developers using coding agents to build on AWS often find that their agents struggle with complex multi-service workflows, rely on outdated knowledge of AWS services, and are difficult to govern — leading to wasted time, wasted tokens, and a reluctance to deploy agents in production. The Agent Toolkit for AWS addresses these challenges through agent skills, a fully-managed MCP server, and easy-to-install plugins. Agent skills give agents validated, up-to-date procedures for tasks like authoring CloudFormation templates, configuring data pipelines, and building serverless applications — so agents follow best practices rather than improvising from general knowledge. Today, we are launching more than 40 skills across infrastructure-as-code, storage, analytics, serverless, containers, and AI services, and we plan to release more in the coming weeks: including for databases, networking, and IAM. Each skill has been rigorously evaluated to ensure that it helps agents complete tasks more accurately and reliably. The AWS MCP Server, now generally available, is a fully-managed MCP server that allows coding agents to interact with any AWS service. It offers IAM-based guardrails on which actions agents can perform, Amazon CloudWatch and AWS CloudTrail observability, and sandboxed code execution for multi-step operations. The AWS MCP server also equips agents with tools to efficiently search and retrieve documentation, so they always have the latest knowledge and guidance. Agent plugins bundle the AWS MCP server and curated sets of skills into a single install. Today, we are releasing three agent plugins: AWS Core, to help application developers build and manage full-stack applications on AWS, AWS Data Analytics, which helps data analysts and business intelligence engineers create data pipelines and load and query data, and AWS Agents, which helps AI engineers build production-ready agents using Amazon Bedrock AgentCore. The MCP servers, skills, and plugins available on AWS Labs will continue to be available, and over time the best of AWS Labs will be transitioned to the Agent Toolkit for AWS to ensure that customers can access the broadest array of tooling and guidance for their agents. The Agent Toolkit for AWS is available at no additional charge; you pay only for the AWS resources your agents use. To learn more, see https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/. To get started, visit the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/quick-start.html or browse the available skills and plugins on https://github.com/aws/agent-toolkit-for-aws.

Now generally available, AWS DevOps Agent is your always-available operations teammate that resolves and proactively prevents incidents, optimizes application reliability and performance, and handles on-demand SRE tasks across AWS, multicloud, and on-prem environments. Building on the preview launch, DevOps Agent now adds new use cases, broader integrations, enhanced intelligence, and enterprise-ready features, including the ability to investigate applications in Azure and on-prem environments, add custom agent skills to extend capabilities, and create custom charts and reports for deeper operational insights. DevOps Agent investigates incidents and identifies operational improvements as an experienced teammate would: by learning your applications and their relationships, working with your observability tools, runbooks, code repositories, and CI/CD pipelines, and correlating telemetry, code, and deployment data. It autonomously triages incidents and guides teams to rapid resolution, reducing mean time to resolution (MTTR) from hours to minutes, while analyzing patterns across historical incidents to deliver actionable recommendations that prevent future outages. For the full list of AWS Regions where AWS DevOps Agent is available, visit the http://docs.aws.amazon.com/devopsagent/latest/userguide/about-aws-devops-agent-supported-regions.html list. Pricing details are available on the AWS DevOps Agenthttps://aws.amazon.com/devops-agent/pricing. AWS Support customers receive monthly DevOps Agent credits based on the prior month's gross AWS Support spend: 100% for Unified Operations, 75% for Enterprise Support, or 30% for Business Support+. For many customers, this significantly reduces or eliminates DevOps Agent costs. For details, visit the https://aws.amazon.com/premiumsupport/plans/. If you are a preview customer, review the https://docs.aws.amazon.com/devopsagent/latest/userguide/configuring-capabilities-for-aws-devops-agent-migrating-from-public-preview-to-general-availability.htmlto ensure seamless access to new AWS DevOps Agent capabilities. To learn more, read the https://aws.amazon.com/blogs/mt/announcing-general-availability-of-aws-devops-agent/ and seehttps://docs.aws.amazon.com/devopsagent/latest/userguide/.

Now generally available, AWS DevOps Agent is your always-available operations teammate that resolves and proactively prevents incidents, optimizes application reliability and performance, and handles on-demand SRE tasks across AWS, multicloud, and on-prem environments. Building on the preview launch, DevOps Agent now adds new use cases, broader integrations, enhanced intelligence, and enterprise-ready features, including the ability to investigate applications in Azure and on-prem environments, add custom agent skills to extend capabilities, and create custom charts and reports for deeper operational insights. DevOps Agent investigates incidents and identifies operational improvements as an experienced teammate would: by learning your applications and their relationships, working with your observability tools, runbooks, code repositories, and CI/CD pipelines, and correlating telemetry, code, and deployment data. It autonomously triages incidents and guides teams to rapid resolution, reducing mean time to resolution (MTTR) from hours to minutes, while analyzing patterns across historical incidents to deliver actionable recommendations that prevent future outages. For the full list of AWS Regions where AWS DevOps Agent is available, visit the Regions list. Pricing details are available on the AWS DevOps Agent pricing page. AWS Support customers receive monthly DevOps Agent credits based on the prior month's gross AWS Support spend: 100% for Unified Operations, 75% for Enterprise Support, or 30% for Business Support+. For many customers, this significantly reduces or eliminates DevOps Agent costs. For details, visit the support compare page. If you are a preview customer, review the migration documentation to ensure seamless access to new AWS DevOps Agent capabilities. To learn more, read the launch blog and see getting started.

Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Model providers and AI researchers building agents that operate on AWS infrastructure need an objective, reproducible way to measure performance and diagnose failures. aws-bench provides a public suite of test cases derived from analysis of real AWS usage, including investigation, troubleshooting, and infrastructure creation tasks. Each test case pairs a natural-language query with a defined cloud resource state and a ground-truth answer, so you can score any agent or model on a consistent, verifiable basis. Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress. The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state. aws-bench is available now on GitHub. To get started, follow the setup instructions on the README.

Amazon Quick connectors let users leverage tools and services such as Outlook, Slack, Salesforce, Jira, and homegrown MCP servers directly into their workflows across chat, agents, apps, flows, and deep research. Today, Amazon Quick introduces new tool settings and MCP sync support that give admins and connector owners more control over how connectors are deployed and kept up to date. Connector owners and admins can now selectively enable or disable individual tools within a connector to ensure only approved tools are available to end users. Additionally, new tool permission settings let connector owners decide which tools require consent before proceeding or give end users the flexibility to decide for themselves. Lastly, MCP sync keeps connectors current as external MCP servers add new tools, update descriptions, and evolve their capabilities, ensuring users always have the latest information to get their work done. These features are available in all AWS Regions where Amazon Quick is available. To learn more, visit the Amazon Quick User Guide.

Today, https://docs.aws.amazon.com/agent-toolkit/latest/userguide/mcp-server.html (AWS MCP Server) added a serverless capability so that coding agents such as Claude Code and Kiro can efficiently diagnose issues with your Lambda functions. The serverless capability helps you troubleshoot your running Lambda functions and their connected resources. The AWS MCP Server, available through the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/ or as a standalone installation, is a managed service that gives AI coding agents secure access to AWS services. With the new AWS MCP Sever serverless capability, your coding agent inspects your Lambda function and its connected resources across Amazon API Gateway, Amazon EventBridge, Amazon S3, Amazon DynamoDB, Amazon SNS, Amazon SQS, and AWS Step Functions. The agent can correlate error signals against a 7-day baseline to pinpoint what changed, surface recurring errors to identify trends, retrieve the deployed configuration of your function and connected resources, provide a timeline of recent changes to track what happened, and analyze service latency across connected resources. As the agent gets comprehensive data in a single call, it consumes fewer tokens compared to orchestrating multiple API calls. To get started, configure the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/ by running ‘aws configure agent-toolkit’ from the AWS CLI, or enable the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/getting-started-aws-mcp-server.html directly. The AWS MCP Server can access services in all commercial https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/, while the AWS MCP Server itself runs in the US East (N. Virginia) and Europe (Frankfurt) Regions. The serverless diagnostic capabilities in the AWS MCP Server are available at no additional cost. To learn more, see the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/capabilities.html.   

Today, AWS announced that the AWS Command Line Interface (CLI) allows users to install the Agent Toolkit for AWS across multiple coding agents with a simple interactive wizard. The Agent Toolkit for AWS gives coding agents the tools, guidance, and guardrails they need to operate safely, effectively, and efficiently on AWS. Starting today, customers can simply type `aws configure agent-toolkit` to install the Agent Toolkit across Kiro, Claude Code, Codex, Cursor, and other popular coding agents. Additionally, customers can now use the AWS CLI to easily search for, install, and manage skills from the Agent Toolkit for AWS to equip their agents with expert guidance to complete tasks. The Agent Toolkit for AWS consists of the AWS MCP Server (which provides a secure, auditable agent interface to 15,000+ AWS APIs), a suite of 40+ agent skills (which give agents expert guidance across storage, networking, analytics, and more), and three plugins (which bundle the MCP server and curate sets of skills into a single install). Using the AWS CLI, customers can now install and configure the MCP server and a customizable set of skills across multiple coding agents via an easy-to-use, interactive wizard. The AWS CLI automatically detects which coding agents are installed and allows users to choose which skills to install for which agents. Customers can then use the CLI to search for available skills, install new skills, and update existing skills.  To get started, see AWS CLI in the Agent Toolkit for AWS user guide. The AWS MCP Server is available in the US East (N. Virginia) and Europe (Frankfurt) Regions.

Amazon Quick connectors let users leverage tools and services such as Outlook, Slack, Salesforce, Jira, and homegrown MCP servers directly into their workflows across chat, agents, apps, flows, and deep research. Today, Amazon Quick introduces new tool settings and MCP sync support that give admins and connector owners more control over how connectors are deployed and kept up to date. Connector owners and admins can now selectively enable or disable individual tools within a connector to ensure only approved tools are available to end users. Additionally, new tool permission settings let connector owners decide which tools require consent before proceeding or give end users the flexibility to decide for themselves. Lastly, MCP sync keeps connectors current as external MCP servers add new tools, update descriptions, and evolve their capabilities, ensuring users always have the latest information to get their work done. These features are available in all AWS Regions where Amazon Quick is available. To learn more, visit the https://docs.aws.amazon.com/quicksight/latest/user/welcome.html.

Today, AWS is launching the Agent Toolkit for AWS, a production-ready suite of tools and guidance that helps AI coding agents build on AWS with fewer errors, lower token costs, and enterprise-grade security controls. The Agent Toolkit for AWS is the successor to the MCP servers, plugins, and skills available on https://github.com/awslabs. Developers using coding agents to build on AWS often find that their agents struggle with complex multi-service workflows, rely on outdated knowledge of AWS services, and are difficult to govern — leading to wasted time, wasted tokens, and a reluctance to deploy agents in production. The Agent Toolkit for AWS addresses these challenges through agent skills, a fully-managed MCP server, and easy-to-install plugins. Agent skills give agents validated, up-to-date procedures for tasks like authoring CloudFormation templates, configuring data pipelines, and building serverless applications — so agents follow best practices rather than improvising from general knowledge. Today, we are launching more than 40 skills across infrastructure-as-code, storage, analytics, serverless, containers, and AI services, and we plan to release more in the coming weeks: including for databases, networking, and IAM. Each skill has been rigorously evaluated to ensure that it helps agents complete tasks more accurately and reliably. The AWS MCP Server, now generally available, is a fully-managed MCP server that allows coding agents to interact with any AWS service. It offers IAM-based guardrails on which actions agents can perform, Amazon CloudWatch and AWS CloudTrail observability, and sandboxed code execution for multi-step operations. The AWS MCP server also equips agents with tools to efficiently search and retrieve documentation, so they always have the latest knowledge and guidance. Agent plugins bundle the AWS MCP server and curated sets of skills into a single install. Today, we are releasing three agent plugins: AWS Core, to help application developers build and manage full-stack applications on AWS, AWS Data Analytics, which helps data analysts and business intelligence engineers create data pipelines and load and query data, and AWS Agents, which helps AI engineers build production-ready agents using Amazon Bedrock AgentCore. The MCP servers, skills, and plugins available on AWS Labs will continue to be available, and over time the best of AWS Labs will be transitioned to the Agent Toolkit for AWS to ensure that customers can access the broadest array of tooling and guidance for their agents. The Agent Toolkit for AWS is available at no additional charge; you pay only for the AWS resources your agents use. To learn more, see https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/. To get started, visit the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/quick-start.html or browse the available skills and plugins on https://github.com/aws/agent-toolkit-for-aws.

Today, AWS announces the public preview of AWS Blocks, an open-source TypeScript framework for application developers who want backend capabilities on AWS removing the need to learn infrastructure tools. AWS Blocks runs a fully functional local environment with Postgres, authentication, and real-time messaging, no AWS account required. When ready to deploy, the same application code runs on production AWS services with zero changes, and developers can drop into AWS CDK at any point for direct resource configuration. A developer building a SaaS application can add database tables, user authentication, AI agents, file uploads, and background jobs in a single session, test the full stack locally, and deploy to AWS when ready. Built-in guidance for AI coding tools enables correct architecture without custom configuration, and end-to-end type safety flows from the data schema to the frontend without a code generation step. At preview, supported frontend frameworks include SPAs (e.g. Vite + React) and SSR frameworks such as Next.js, Nuxt, and Astro. AWS Blocks is available at no additional charge. You pay only for the AWS services your application uses. AWS Blocks deploys to all commercial AWS regions. To get started, run npx @aws-blocks/create-blocks-app. Read more here: AWS Blocks product page Getting started guide in the AWS Blocks Developer Guide AWS Blocks on GitHub

The Amazon Quick desktop app is now generally available on macOS and Windows. The desktop app brings the full power of Amazon Quick to your computer, working directly with your local files and staying connected to your calendar, email, and business apps in the background. Quick keeps your conversations, context, and agents synchronized across the desktop and mobile applications, so work you start on one surface carries over to the other, enabling you to work wherever you want.  Additionally, with this release, Amazon Quick agents run continuously in the background, even after you close your computer, so long-running work keeps making progress while you're away. Start an agent before you leave the office, provide additional inputs from the mobile app during your commute home, and then review the final output when you arrive. Quick offers production-grade stability, maintains AWS SLA commitments, and offers the governance and administrative controls for deployments at enterprise scale.  The Amazon Quick desktop app is available in 7 regions, US East (N. Virginia), Asia Pacific (Sydney), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Tokyo), and Europe (Frankfurt)  Existing Quick users can download the desktop app from here. The Quick mobile application is available for free from the Apple App Store and Google Play Store.

The Amazon Quick desktop app is now generally available on macOS and Windows. The desktop app brings the full power of Amazon Quick to your computer, working directly with your local files and staying connected to your calendar, email, and business apps in the background. Quick keeps your conversations, context, and agents synchronized across the desktop and mobile applications, so work you start on one surface carries over to the other, enabling you to work wherever you want.  Additionally, with this release, Amazon Quick agents run continuously in the background, even after you close your computer, so long-running work keeps making progress while you're away. Start an agent before you leave the office, provide additional inputs from the mobile app during your commute home, and then review the final output when you arrive. Quick offers production-grade stability, maintains AWS SLA commitments, and offers the governance and administrative controls for deployments at enterprise scale.  The Amazon Quick desktop app is available in 7 regions, US East (N. Virginia), Asia Pacific (Sydney), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Tokyo), and Europe (Frankfurt)  Existing Quick users can download the desktop app from https://aws.amazon.com/quick/download/. The Quick mobile application is available for free from the https://apps.apple.com/us/app/amazon-quick/id1148226615 and https://play.google.com/store/apps/details?id=com.amazonaws.quicksight.mobile&hl=en_US.

Today, AWS announces the general availability of the AWS MCP Server, a managed server that gives AI coding agents secure, auditable access to AWS services through the Model Context Protocol (MCP). The AWS MCP Server is a core component of the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/, which helps coding agents build on AWS more effectively. With the AWS MCP Server, organizations can let coding agents interact with AWS while maintaining visibility and control through IAM-based guardrails, Amazon CloudWatch metrics, and AWS CloudTrail logging. Since the preview launch at re:Invent 2025, the AWS MCP Server has added several capabilities. Agents can now call any AWS API through a single tool, including operations that require file uploads or long-running execution. Sandboxed script execution lets agents run Python code against AWS services for multi-step operations, without access to your local filesystem or shell tools. Agent skills replace agent SOPs with a more flexible format: agents discover and load curated guidance on demand, keeping context window usage low while providing tested procedures for complex tasks. Additionally, documentation search and skill discovery no longer require AWS credentials, removing a common barrier to getting started. The AWS MCP Server is available at no additional charge; you pay only for the AWS resources your agents use. To learn more, see https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/. To get started, visit the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/quick-start.html.

Today, AWS announced that the AWS Command Line Interface (CLI) allows users to install the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/ across multiple coding agents with a simple interactive wizard. The Agent Toolkit for AWS gives coding agents the tools, guidance, and guardrails they need to operate safely, effectively, and efficiently on AWS. Starting today, customers can simply type `aws configure agent-toolkit` to install the Agent Toolkit across Kiro, Claude Code, Codex, Cursor, and other popular coding agents. Additionally, customers can now use the AWS CLI to easily search for, install, and manage skills from the Agent Toolkit for AWS to equip their agents with expert guidance to complete tasks. The Agent Toolkit for AWS consists of the AWS MCP Server (which provides a secure, auditable agent interface to 15,000+ AWS APIs), a suite of 40+ agent skills (which give agents expert guidance across storage, networking, analytics, and more), and three plugins (which bundle the MCP server and curate sets of skills into a single install). Using the AWS CLI, customers can now install and configure the MCP server and a customizable set of skills across multiple coding agents via an easy-to-use, interactive wizard. The AWS CLI automatically detects which coding agents are installed and allows users to choose which skills to install for which agents. Customers can then use the CLI to search for available skills, install new skills, and update existing skills.  To get started, see https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html in the Agent Toolkit for AWS user guide. The AWS MCP Server is available in the US East (N. Virginia) and Europe (Frankfurt) Regions.

Today, AWS Transform announces a new continuous modernization capability (Preview) that autonomously detects, prioritizes, and remediates tech debt across enterprise software portfolios.  AWS Transform already helps enterprises migrate out of data centers, modernize mainframe and Windows applications, and modernize codebases for common scenarios such as version upgrades, runtime or API migrations, language translations, and Lambda run-time upgrades. With this new capability, we are now simplifying how customers manage their software tech debt, enabling them to move from manual maintenance to keeping their codebases always up to date. It also provides the ability to assess and remediate your code bases for AI agents. Now customers can easily get full visibility to the status of their codebase across thousands of repositories, better prioritize the issues, and schedule automatic remediation with human oversight. Transform – continuous modernization also supports analyses such as agentic readiness and modernization readiness. In addition, it integrates with AWS Security Agent to detect and remediate security vulnerabilities at the source code level.  To get started, customers can use the AWS Transform web console, CLI, AWS Transform Kiro power, or use the AWS Transform skill in other coding agents. After connecting their source code from GitHub, GitLab, Bitbucket or other sources, customers can run an analysis in their IDE, track progress in the AWS Transform web console, and review findings wherever it makes sense, with job state and context shared across every surface. AWS Transform - continuous modernization is now available in US East (N. Virginia) and Europe (Frankfurt) https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/.  To learn more, visit the AWS Transform https://aws.amazon.com/transform/, https://docs.aws.amazon.com/transform/latest/userguide/what-is-service.html, and https://aws.amazon.com/transform/pricing/, for the latest details.

Today, AWS announces the public preview of AWS Blocks, an open-source TypeScript framework for application developers who want backend capabilities on AWS removing the need to learn infrastructure tools. AWS Blocks runs a fully functional local environment with Postgres, authentication, and real-time messaging, no AWS account required. When ready to deploy, the same application code runs on production AWS services with zero changes, and developers can drop into AWS CDK at any point for direct resource configuration. A developer building a SaaS application can add database tables, user authentication, AI agents, file uploads, and background jobs in a single session, test the full stack locally, and deploy to AWS when ready. Built-in guidance for AI coding tools enables correct architecture without custom configuration, and end-to-end type safety flows from the data schema to the frontend without a code generation step. At preview, supported frontend frameworks include SPAs (e.g. Vite + React) and SSR frameworks such as Next.js, Nuxt, and Astro. AWS Blocks is available at no additional charge. You pay only for the AWS services your application uses. AWS Blocks deploys to all commercial AWS regions. To get started, run npx @aws-blocks/create-blocks-app. Read more here: https://aws.amazon.com/products/developer-tools/blocks/ https://docs.aws.amazon.com/blocks/latest/devguide/getting-started.html in the AWS Blocks Developer Guide https://github.com/aws-devtools-labs/aws-blocks

Today, AWS announces the general availability of the AWS MCP Server, a managed server that gives AI coding agents secure, auditable access to AWS services through the Model Context Protocol (MCP). The AWS MCP Server is a core component of the https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/, which helps coding agents build on AWS more effectively. With the AWS MCP Server, organizations can let coding agents interact with AWS while maintaining visibility and control through IAM-based guardrails, Amazon CloudWatch metrics, and AWS CloudTrail logging. Since the preview launch at re:Invent 2025, the AWS MCP Server has added several capabilities. Agents can now call any AWS API through a single tool, including operations that require file uploads or long-running execution. Sandboxed script execution lets agents run Python code against AWS services for multi-step operations, without access to your local filesystem or shell tools. Agent skills replace agent SOPs with a more flexible format: agents discover and load curated guidance on demand, keeping context window usage low while providing tested procedures for complex tasks. Additionally, documentation search and skill discovery no longer require AWS credentials, removing a common barrier to getting started. The AWS MCP Server is available at no additional charge; you pay only for the AWS resources your agents use. To learn more, see https://aws.amazon.com/products/developer-tools/agent-toolkit-for-aws/. To get started, visit the https://docs.aws.amazon.com/agent-toolkit/latest/userguide/quick-start.html.

AWS announces the launch of deployment Standard Operating Procedures (SOPs) available in the https://docs.aws.amazon.com/aws-mcp/latest/userguide/what-is-mcp-server.html. SOPs are structured, natural language instructions that guide AI agents through complex, multi-step tasks to ensure consistent, reliable, and efficient behavior. With these automated procedures, customers can deploy web applications to their AWS account using natural language prompts from any MCP-compatible IDE or CLI, including Kiro, Kiro CLI, Cursor, and Claude Code. Deployment works by generating AWS CDK infrastructure, deploying CloudFormation stacks, and creating CI/CD pipelines with recommended AWS security best practices. Previously, developers struggled to take their vibe-coded applications to production with DevOps best practices in place. Now, developers can move quickly from prototype to production in as little as one prompt. When you ask your AI assistant configured with AWS MCP Server to deploy your web application, your AI agent will follow the multi-step plan defined in Agent SOPs to analyze the project structure, generate CDK infrastructure, and deploy a preview environment hosted on Amazon S3 and Amazon CloudFront. Once you are ready, it can configure AWS CodePipeline for automated production deployments from source repositories, setting up CI/CD automatically for your application. The Agent SOPs support web applications built with popular frameworks including React, Vue.js, Angular, and Next.js. Deployment documentation is automatically created in the repository, enabling agents to handle future deployments, query logs for troubleshooting and resume work across sessions. The Agent SOPs are available in preview as part of the AWS MCP Server at no additional cost in the US East (N. Virginia) Region. You pay only for AWS resources you create and applicable data transfer costs. To get started, see the https://docs.aws.amazon.com/aws-mcp/latest/userguide/agent-sops-deployment.html.

Today, AWS announces the general availability of the https://docs.aws.amazon.com/cdk/v2/guide/toolkit-library.html, a Node.js library that provides programmatic access to core AWS CDK functionalities such as synthesis, deployment, and destruction of stacks. This library enables developers to integrate CDK operations directly into their applications, custom CLIs, and automation workflows, offering greater flexibility and control over infrastructure management. Prior to this release, interacting with CDK required using the CDK CLI, which could present challenges when integrating CDK actions into automated workflows or custom tools. With the CDK Toolkit Library, developers can now build custom CLIs, integrate CDK actions in their existing CI/CD workflows, programmatically enforce guardrails and policies, and manage ephemeral environments. The AWS CDK Toolkit Library is available in all AWS Regions where the AWS CDK is supported. For more information and a walkthrough of the feature, check out the https://community.aws/content/2wm6TNpUlPMVgcvXVySywxWaO7T. To get started with the CDK Toolkit Library, please find the documentation https://docs.aws.amazon.com/cdk/v2/guide/toolkit-library.html.  

Today, AWS Transform announces a new continuous modernization capability (Preview) that autonomously detects, prioritizes, and remediates tech debt across enterprise software portfolios.  AWS Transform already helps enterprises migrate out of data centers, modernize mainframe and Windows applications, and modernize codebases for common scenarios such as version upgrades, runtime or API migrations, language translations, and Lambda run-time upgrades. With this new capability, we are now simplifying how customers manage their software tech debt, enabling them to move from manual maintenance to keeping their codebases always up to date. It also provides the ability to assess and remediate your code bases for AI agents. Now customers can easily get full visibility to the status of their codebase across thousands of repositories, better prioritize the issues, and schedule automatic remediation with human oversight. Transform – continuous modernization also supports analyses such as agentic readiness and modernization readiness. In addition, it integrates with AWS Security Agent to detect and remediate security vulnerabilities at the source code level.  To get started, customers can use the AWS Transform web console, CLI, AWS Transform Kiro power, or use the AWS Transform skill in other coding agents. After connecting their source code from GitHub, GitLab, Bitbucket or other sources, customers can run an analysis in their IDE, track progress in the AWS Transform web console, and review findings wherever it makes sense, with job state and context shared across every surface. AWS Transform - continuous modernization is now available in US East (N. Virginia) and Europe (Frankfurt) AWS Regions.  To learn more, visit the AWS Transform webpage, user guide, and pricing, for the latest details.

Today, AWS announced cross-account and cross-role access for the AWS Model Context Protocol (MCP) Server, part of the Agent Toolkit for AWS. This feature allows developers using AI coding agents like Kiro, Claude Code, or Codex to work across multiple AWS accounts and AWS Identity and Access Management (IAM) roles within a single session, with no restarts required. Previously, switching profiles required stopping the AI coding session, updating local AWS credentials, and restarting the MCP server for every account change. Now, AI agents using the AWS MCP Server can specify a profile on each command, allowing users to switch between accounts and roles seamlessly. Cross-account access helps developers move faster across multi-account environments. For example, a DevOps engineer can query CloudWatch logs across production and staging accounts to diagnose a performance issue, or an application developer can update a Lambda configuration in one account and adjust an S3 bucket policy in another, all within the same conversation. Each request specifies which profile to use, so there is no risk of commands reaching the wrong account. To get started, see Multi-profile support in the Agent Toolkit for AWS user guide. The AWS MCP Server is available in the US East (N. Virginia) and Europe (Frankfurt) Regions.

Today, AWS announces the general availability of the AWS MCP Server, a managed server that gives AI coding agents secure, auditable access to AWS services through the Model Context Protocol (MCP). The AWS MCP Server is a core component of the Agent Toolkit for AWS, which helps coding agents build on AWS more effectively. With the AWS MCP Server, organizations can let coding agents interact with AWS while maintaining visibility and control through IAM-based guardrails, Amazon CloudWatch metrics, and AWS CloudTrail logging. Since the preview launch at re:Invent 2025, the AWS MCP Server has added several capabilities. Agents can now call any AWS API through a single tool, including operations that require file uploads or long-running execution. Sandboxed script execution lets agents run Python code against AWS services for multi-step operations, without access to your local filesystem or shell tools. Agent skills replace agent SOPs with a more flexible format: agents discover and load curated guidance on demand, keeping context window usage low while providing tested procedures for complex tasks. Additionally, documentation search and skill discovery no longer require AWS credentials, removing a common barrier to getting started. The AWS MCP Server is available at no additional charge; you pay only for the AWS resources your agents use. To learn more, see Agent Toolkit for AWS. To get started, visit the Agent Toolkit for AWS Quick Start guide.