Launched in 2025
Pricing
Free trial
Free version

Kiro is an AI-integrated development environment created by Amazon Web Services. It introduces a spec-driven development workflow in which a developer's prompt is first expanded into a requirements document, then a design document, and finally a set of implementation tasks that AI agents execute. This structured approach aims to reduce ambiguity and keep AI-generated code aligned with the original intent throughout the development lifecycle. Kiro includes an agentic coding assistant, automated hooks that run on file-save events to enforce linting, testing, and documentation, and a steering-rules system that lets teams encode project-wide conventions the AI must follow. It is built on the VS Code open-source foundation, supports standard VS Code extensions, and connects to Model Context Protocol (MCP) servers for external tool access. Kiro was made available as a free preview in July 2025 and targets individual developers as well as development teams looking to accelerate software delivery with AI assistance.

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Target audience and deployment

  • Solo / Freelancer
  • Startup
  • SMB
  • Mid-market
  • Enterprise
  • Cloud

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Key features

Spec-driven development workflowAI agentic coding assistantAutomated hooks on file saveSteering rules for project conventionsRequirements document generationDesign document generationTask list generation and executionModel Context Protocol (MCP) server supportVS Code extension compatibilityChat and inline code editing

Use cases

  • Generate production-ready code from natural language prompts
  • Enforce project-wide coding conventions with steering rules
  • Automate repetitive tasks on file save with hooks
  • Collaborate with AI agents on multi-step software design
  • Extend IDE capabilities via MCP servers

Best for

  • Individual developers who need to accelerate feature delivery with AI-assisted coding
  • Development teams who need to enforce consistent coding standards across AI-generated code
  • Software engineers who need to translate product requirements into implementation tasks automatically

Integrations

AI models included

Amazon Bedrock, Claude

Other

Model Context Protocol (MCP)