Bedrock AgentCore SDK

Deploy your local AI agent to Bedrock AgentCore with zero infrastructure

Documentation ◆ Samples ◆ Discord ◆ Boto3 Python SDK ◆ Runtime Python SDK ◆ Starter Toolkit

Overview

Amazon Bedrock AgentCore enables you to deploy and operate highly effective agents securely, at scale using any framework and model. With Amazon Bedrock AgentCore, developers can accelerate AI agents into production with the scale, reliability, and security, critical to real-world deployment. AgentCore provides tools and capabilities to make agents more effective and capable, purpose-built infrastructure to securely scale agents, and controls to operate trustworthy agents. Amazon Bedrock AgentCore services are composable and work with popular open-source frameworks and any model, so you don’t have to choose between open-source flexibility and enterprise-grade security and reliability.

🚀 From Local Development to Bedrock AgentCore

# Your existing agent (any framework)
from strands import Agent
# or LangGraph, CrewAI, Autogen, custom logic - doesn't matter

def my_local_agent(query):
    # Your carefully crafted agent logic
    return agent.process(query)

# Deploy to Bedrock AgentCore
from bedrock_agentcore import BedrockAgentCoreApp
app = BedrockAgentCoreApp()

@app.entrypoint
def production_agent(request):
    return my_local_agent(request.get("prompt"))  # Same logic, enterprise platform

app.run()  # Ready to run on Bedrock AgentCore

What you get with Bedrock AgentCore:

✅ Keep your agent logic - Works with Strands, LangGraph, CrewAI, Autogen, custom frameworks
✅ Zero infrastructure management - No servers, containers, or scaling concerns
✅ Enterprise-grade platform - Built-in auth, memory, observability, security
✅ Production-ready deployment - Reliable, scalable, compliant hosting

Amazon Bedrock AgentCore services

🚀 Runtime - Secure and session isolated compute: Runtime Quick Start
🧠 Memory - Persistent knowledge across sessions: Memory Quick Start
🔗 Gateway - Transform APIs into MCP tools: Gateway Quick Start
💻 Code Interpreter - Secure sandboxed execution: Code Interpreter Quick Start
🌐 Browser - Cloud-based web automation: Browser Quick Start
📊 Observability - OpenTelemetry tracing: Observability Quick Start
🔐 Identity - AWS & third-party auth: Identity Quick Start

🏗️ Deployment

Quick Start: Use the Bedrock AgentCore Starter Toolkit for rapid prototyping.

Production: AWS CDK - coming soon.

⚠️ Preview Status

Bedrock AgentCore SDK is currently in public preview. APIs may change as we refine the SDK.

📝 License & Contributing

License: Apache 2.0 - see LICENSE.txt
Contributing: See CONTRIBUTING.md
Security: Report vulnerabilities via SECURITY.md

Metadata

Release files for bedrock-agentcore 0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bedrock-agentcore 0.1.7
File	Size	Uploaded
bedrock_agentcore-0.1.7.tar.gz	263.1 kB	Oct 1, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for bedrock-agentcore 0.1.7
File	Interpreter	ABI	Platform	Reset
bedrock_agentcore-0.1.7-py3-none-any.whl 77.2 kB Oct 1, 2025	Python 3	none	any	Details

Total release size: 340.3 kB

Release files / bedrock_agentcore-0.1.7.tar.gz

Download URL	bedrock_agentcore-0.1.7.tar.gz
Size	263.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`e518e8f5e6fb5a5a80182db95757a20e32b0ac2b33d0a1909dfafcba950c6356`
BLAKE2b-256 checksum How to use checksums	`b0874c0bacf09430e559657fc986cbb1003f76d597ab7e7365ab247dbef73940`
Upload date	Oct 1, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.7`

Release files / bedrock_agentcore-0.1.7-py3-none-any.whl

Download URL	bedrock_agentcore-0.1.7-py3-none-any.whl
Size	77.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`441dde64fea596e9571e47ae37ee3b033e58d8d255018f13bdcde8ae8bef2075`
BLAKE2b-256 checksum How to use checksums	`01f3a9d961cfba236dc85f27f2f2c6eab88e12698754aaa02459ba7dfafc5062`
Upload date	Oct 1, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.7`