aws/bedrock-agentcore-starter-toolkit
Python CLI toolkit for Amazon Bedrock AgentCore (legacy). For new projects, use the AgentCore CLI: https://github.com/aws/agentcore-cli
What it solves
It simplifies the process of building, deploying, and operating production-ready AI agents on Amazon Bedrock AgentCore. It provides a set of tools to help developers move agents from development to a secure, scalable, and reliable production environment without having to manage the underlying infrastructure.
How it works
This toolkit acts as a starting point for developers to create projects using various agent SDK frameworks (such as Strands, LangGraph, or LangChain) and model providers. It integrates with a suite of modular Bedrock AgentCore services, including:
- Runtime: A serverless environment for deploying agents and tools.
- Memory: Managed short-term and long-term memory for context-aware conversations.
- Gateway: A managed Model Context Protocol (MCP) server that converts APIs and Lambda functions into tools.
- Code Interpreter: A secure sandbox for executing code.
- Browser: A cloud-based browser for interacting with websites.
- Observability & Evaluation: Tools for tracing, debugging, and measuring agent performance metrics like correctness and goal success.
- Identity & Policy: Systems for secure access management and deterministic control over agent actions using the Cedar policy language.
Who it’s for
Developers who want to build AI agents using open-source frameworks and deploy them to Amazon Bedrock AgentCore, specifically those who prefer a Python-based workflow (though the project now recommends the AgentCore CLI for new projects).
Highlights
- Framework Agnostic: Works with popular frameworks like LangGraph, CrewAI, and Strands.
- Serverless Scaling: Handles infrastructure and security via the AgentCore Runtime.
- MCP Integration: Uses the Gateway service to scale agents to use hundreds or thousands of tools.
- Enterprise Security: Includes built-in identity management and a secure code execution sandbox.
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