Port AgentCoreMemoryStore (MemoryStore interface) from TypeScript SDK to Python

Start by reading the TypeScript implementation under bedrock-agentcore/memory/integrations/strands and compare it with the Python AgentCoreMemorySessionManager. Add the Python memory_store.py entry points and factory described in the issue, mapping search and add_messages to AgentCore Memory. Done means Python users can pass the created stores to Strands MemoryManager for recall, injection, and extraction.

Problem Statement

The TypeScript bedrock-agentcore SDK (v0.4.1+) ships an AgentCoreMemoryStore that implements the Strands MemoryStore interface, enabling AgentCore Memory to plug into the MemoryManager pipeline with recall (search tool), injection (automatic prompt augmentation), and server-side extraction. It is documented on the Strands integrations page: https://strandsagents.com/docs/integrations/memory-stores/agentcore-memory-store/

The Python bedrock-agentcore SDK currently only integrates AgentCore Memory as a session manager (AgentCoreMemorySessionManager). There is no MemoryStore implementation, so Python developers cannot use AgentCore Memory with MemoryManager.

Proposed Solution

Port the AgentCoreMemoryStore from the TypeScript SDK to Python. The integration lives at bedrock-agentcore/memory/integrations/strands/ in the TS package and maps:

• search to AgentCore's retrieveMemoryRecords
• add_messages to conversation ingestion for server-side extraction
• Per-namespace store creation via a create_agentcore_memory_stores factory

Target usage:

from strands import Agent
from strands.memory import MemoryManager
from bedrock_agentcore.memory.integrations.strands.memory_store import (
    AgentCoreMemoryStore,
    create_agentcore_memory_stores,
)

stores = create_agentcore_memory_stores(
    memory_id="mem-abc",
    actor_id="user-123",
    session_id="session-1",
    namespaces=[
        {"namespace": "/facts/{actorId}", "writable": True},
        {"namespace": "/preferences/{actorId}"},
    ],
    extraction=True,
)

agent = Agent(memory_manager=MemoryManager(stores=stores))

Use Case

Python agents that want to use AgentCore Memory as a long-term memory backend through the standard MemoryManager pipeline, with injection, recall tools, and extraction.

Additional Context

• TypeScript implementation: https://github.com/aws/bedrock-agentcore-sdk-typescript/tree/main/src/memory/integrations/strands
• Strands integration page (TS only): https://strandsagents.com/docs/integrations/memory-stores/agentcore-memory-store/
• The existing Python AgentCoreMemorySessionManager would remain for session persistence use cases. The MemoryStore is complementary.