A model-driven approach to building AI agents in just a few lines of code.

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

A set of tools that gives agents powerful capabilities.

Natural language workflows that enable AI agents to perform complex, multi-step tasks with consistency and reliability.

Agent samples built using the Strands Agents SDK.

A model-driven approach to building AI agents in just a few lines of code.

An example agent demonstrating streaming, tool use, and interactivity from your terminal. This agent builder can help you to build your own agents and tools.

This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite AI coding assistant to vibe-code Strands Agents.

Python functions powered by AI agents - with runtime post-conditions for reliable agentic workflows.

Build Agentic AI solutions on AWS, using latest OSS Agentic Frameworks.

Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB

Documentation for the Strands Agents SDK. A model-driven approach to building AI agents in just a few lines of code.

Reference architecture for agentic AI chatbots with Strands Agents and Amazon Bedrock AgentCore

A comprehensive evaluation framework for AI agents and LLM applications.

Agent Skills implementation for Strands Agents SDK

Learn to build AI agents with Strands framework. Covers LLM integration via Amazon Bedrock/Anthropic, AWS service connections, tool implementation with MCP/A2A protocols, and agent evaluation using LangFuse/RAGAS.

SGLang model provider for Strands Agents for on-policy agentic RL training.

A full-stack AI chat application powered by Amazon Bedrock and Strands Agents

Control robots and physical hardware with natural language through Strands Agents.

Amazon Bedrock AgentCore – Multi Framework Examples