Amazon Bedrock Memory gives Kiro CLI persistent conversations across sessions

Agentic IDEs like Kiro CLI often lack memory across sessions, forcing developers to re-explain context each time. Amazon Bedrock AgentCore Memory now solves this by providing a fully managed, persistent memory with semantic search. The solution comprises three components: Bedrock AgentCore Memory for storing and retrieving conversation data, a custom MCP server that exposes memory operations as tools (conversation, monitoring, management), and Kiro CLI which connects to the server via STDIO. The MCP server uses a two-stage retrieval strategy: first semantic search via Bedrock's API, then fallback to direct content matching. This ensures conversations are findable even before semantic indexing completes. Developers can query by timeframe (e.g., 'yesterday') or topic.

The walkthrough requires an AWS account, Kiro CLI installed, and cloning the sample repository. Setup involves creating a virtual environment, installing dependencies, and running a Python script to create the Bedrock AgentCore memory resource and generate Kiro agent config. The MCP server provides tools for storing, retrieving, listing, and deleting sessions, as well as monitoring memory usage. This architecture transforms Kiro CLI into a context-aware assistant that remembers project details, preferences, and workflows across terminal sessions, eliminating repetitive context-setting and greatly improving developer productivity.