Create an AgentCore Memory - Amazon Bedrock AgentCore

Create an AgentCore Memory

You can create an AgentCore Memory with the Amazon Bedrock AgentCore starter toolkit, AgentCore python SDK, the AWS console, or with the CreateMemory AWS SDK operation. When creating a memory, you can configure settings such as name, description, encryption settings, expiration timestamp for raw events, and memory strategies if you want to extract long-term memory.

When creating an AgentCore Memory, consider the following factors to maintain it meets your application's needs:

Event retention – Choose how long raw events are retained (up to 365 days) for short-term memory.

Security requirements – If your application handles sensitive information, consider using a customer managed AWS KMS key for encryption. The service still encrypts data using a service managed key, even if you don't provide a customer-managed AWS KMS key.

Memory strategies – Define how events are processed into meaningful long-term memories using built-in or built-in with overrides strategies. If you do not define any strategy, only short-term memory containing raw events are stored. For more information, see Use long-term memory.

Naming conventions – Use clear, descriptive names that help identify the purpose of each AgentCore Memory, especially if your application uses multiple stores.

Starter toolkit CLI

Create a basic memory (short-term only):

agentcore memory create my_agent_memory --region us-west-2

Create memory with long-term strategies:

agentcore memory create ShoppingSupportAgentMemory \
  --region us-west-2 \
  --description "Memory for a customer support agent." \
  --strategies '[{"summaryMemoryStrategy": {"name": "SessionSummarizer", "namespaces": ["/summaries/{actorId}/{sessionId}"]}}, {"userPreferenceMemoryStrategy": {"name": "PreferenceLearner", "namespaces": ["/users/{actorId}/preferences"]}}]' \
  --wait

List all memories:

agentcore memory list --region us-west-2

Get memory details:

agentcore memory get <memory-id> --region us-west-2

Check memory status:

agentcore memory status <memory-id> --region us-west-2
Starter toolkit

for the full example, see Get started with AgentCore Memory.


from bedrock_agentcore_starter_toolkit.operations.memory.manager import MemoryManager
from bedrock_agentcore.memory.session import MemorySessionManager
from bedrock_agentcore.memory.constants import ConversationalMessage, MessageRole
from bedrock_agentcore_starter_toolkit.operations.memory.models.strategies import SummaryStrategy, UserPreferenceStrategy
import time

# Create memory manager
memory_manager = MemoryManager(region_name="us-west-2")

print("Creating a new memory resource and waiting for it to become active...")

# Create memory resource with summary and user preference strategy
memory = memory_manager.get_or_create_memory(
    name="ShoppingSupportAgentMemory",
    description="Memory for a customer support agent.",
    strategies=[
        SummaryStrategy(
            name="SessionSummarizer",
            namespaces=["/summaries/{actorId}/{sessionId}"]
        ),
        UserPreferenceStrategy(
            name="PreferenceLearner",
            namespaces=["/users/{actorId}/preferences"]
        )
    ]
)

memory_id = memory.get('id')
print(f"Memory resource is now ACTIVE with ID: {memory_id}")
AgentCore python SDK

For more information, see Amazon Bedrock AgentCore SDK.

from bedrock_agentcore.memory import MemoryClient
import time

client = MemoryClient(region_name="us-east-1")

memory = client.create_memory_and_wait(
    name="MyAgentMemory",
    strategies=[{
        "summaryMemoryStrategy": {
            # Name of the extraction model/strategy
            "name": "SessionSummarizer",
            # Organize facts by session ID for easy retrieval
            # Example: "summaries/session123" contains summary of session123
            "namespaces": ["/summaries/{actorId}/{sessionId}"]
        }
    }]
)
AWS SDK

For more information, see AWS SDK.

import boto3
import time

# Initialize the Boto3 clients for control plane and data plane operations
control_client = boto3.client('bedrock-agentcore-control')
data_client = boto3.client('bedrock-agentcore')

print("Creating a new memory resource...")

# Create the memory resource with defined strategies
response = control_client.create_memory(
    name="ShoppingSupportAgentMemory",
    description="Memory for a customer support agent.",
    memoryStrategies=[
        {
            'summaryMemoryStrategy': {
                'name': 'SessionSummarizer',
                'namespaces': ['/summaries/{actorId}/{sessionId}']
            }
        },
        {
            'userPreferenceMemoryStrategy': {
                'name': 'UserPreferenceExtractor',
                'namespaces': ['/users/{actorId}/preferences']
            }
        }
    ]
)

memory_id = response['memory']['id']
print(f"Memory resource created with ID: {memory_id}")

# Poll the memory status until it becomes ACTIVE
while True:
    mem_status_response = control_client.get_memory(memoryId=memory_id)
    status = mem_status_response.get('memory', {}).get('status')
    if status == 'ACTIVE':
        print("Memory resource is now ACTIVE.")
        break
    elif status == 'FAILED':
        raise Exception("Memory resource creation FAILED.")
    print("Waiting for memory to become active...")
    time.sleep(10)
Console
To create an AgentCore memory

  1. Open the Amazon Bedrock AgentCore console.

  2. In the left navigation pane, choose Memory.

  3. Choose Create memory.

  4. For Memory name enter a name for the AgentCore Memory.

  5. (Optional) For Short-term memory (raw event) expiration set the duration (days), for which the AgentCore Memory will store events.

  6. (Optional) In Additional configurations set the following:

    1. For Memory description, enter a description for the AgentCore Memory.

    2. If you want to use your own AWS KMS key to encrypt your data, do the following:

      1. In KMS key, choose Customize encryption settings (advanced).

      2. In Choose an AWS KMS key choose or enter the ARN of an existing AWS KMS key. Alternatively, choose Create an AWS KMS to create a new AWS KMS key.

  7. (Optional) For Long-term memory extraction strategies choose one or more memory strategies. For more information:

  8. Choose Create memory to create the AgentCore Memory.