AWS Bedrock AgentCore

Build production-grade AI agents on AWS infrastructure.

Quick Start import boto3 from agentcore import Agent, Tool

Initialize AgentCore client

client = boto3.client('bedrock-agent-runtime')

Define a tool

@Tool(name="search_database", description="Search the product database") def search_database(query: str, limit: int = 10) -> dict: # Tool implementation return {"results": [...]}

Create agent

agent = Agent( model_id="anthropic.claude-3-sonnet", tools=[search_database], instructions="You are a helpful product search assistant." )

Invoke agent

response = agent.invoke("Find laptops under $1000")

AgentCore Components

AgentCore provides these primitives:

Component Purpose Runtime Serverless agent execution (framework-agnostic) Gateway Convert APIs/Lambda to MCP-compatible tools Memory Multi-strategy memory (semantic, user preference) Identity Auth with Cognito, Okta, Google, EntraID Tools Code Interpreter, Browser Tool Observability Deep analysis and tracing Lambda Tool Integration

Lambda function as tool

import json

def lambda_handler(event, context): action = event.get('actionGroup') function = event.get('function') parameters = event.get('parameters', [])

# Parse parameters
params = {p['name']: p['value'] for p in parameters}

if function == 'get_weather':
    result = get_weather(params['city'])
elif function == 'book_flight':
    result = book_flight(params['origin'], params['destination'])

return {
    'response': {
        'actionGroup': action,
        'function': function,
        'functionResponse': {
            'responseBody': {
                'TEXT': {'body': json.dumps(result)}
            }
        }
    }
}

Agent Orchestration from agentcore import SupervisorAgent, SubAgent

Create specialized sub-agents

research_agent = SubAgent( name="researcher", model_id="anthropic.claude-3-sonnet", instructions="You research and gather information." )

writer_agent = SubAgent( name="writer", model_id="anthropic.claude-3-sonnet", instructions="You write clear, engaging content." )

Create supervisor

supervisor = SupervisorAgent( model_id="anthropic.claude-3-opus", sub_agents=[research_agent, writer_agent], routing_strategy="supervisor" # or "intent_classification" )

response = supervisor.invoke("Write a blog post about AI agents")

Guardrails Integration from agentcore import Agent, Guardrail

Define guardrail

guardrail = Guardrail( guardrail_id="my-guardrail-id", guardrail_version="1" )

agent = Agent( model_id="anthropic.claude-3-sonnet", guardrails=[guardrail], tools=[...], )

AgentCore Gateway

Convert existing APIs to MCP-compatible tools:

gateway_setup.py

from bedrock_agentcore import GatewayClient

gateway = GatewayClient()

Create gateway from OpenAPI spec

gateway.create_target( name="my-api", type="OPENAPI", openapi_spec_path="./api-spec.yaml" )

Create gateway from Lambda function

gateway.create_target( name="my-lambda-tool", type="LAMBDA", function_arn="arn:aws:lambda:us-east-1:123456789:function:my-tool" )

AgentCore Memory from agentcore import Agent, Memory

Create memory with multiple strategies

memory = Memory( name="customer-support-memory", strategies=["semantic", "user_preference"] )

agent = Agent( model_id="anthropic.claude-3-sonnet", memory=memory, tools=[...], )

Memory persists across sessions

response = agent.invoke( "What did we discuss last time?", session_id="user-123" )

Official Use Cases Repository

AWS provides production-ready implementations:

Repository: https://github.com/awslabs/amazon-bedrock-agentcore-samples

Available Use Cases (02-use-cases/) Use Case Description A2A Multi-Agent Incident Response Agent-to-Agent with Strands + OpenAI SDK Customer Support Assistant Memory, Knowledge Base, Google OAuth Market Trends Agent LangGraph with browser tools DB Performance Analyzer PostgreSQL integration Device Management Agent IoT with Cognito auth Enterprise Web Intelligence Browser tools for research Text to Python IDE AgentCore Code Interpreter Video Games Sales Assistant Amplify + CDK deployment Quick Start with Use Cases git clone https://github.com/awslabs/amazon-bedrock-agentcore-samples.git cd amazon-bedrock-agentcore-samples/02-use-cases/customer-support-assistant

Follow README for deployment

Resources Official Samples: https://github.com/awslabs/amazon-bedrock-agentcore-samples Use Cases: https://github.com/awslabs/amazon-bedrock-agentcore-samples/tree/main/02-use-cases Tutorials: https://github.com/awslabs/amazon-bedrock-agentcore-samples/tree/main/01-tutorials

aws-agentcore

安装