Extending conversational memory in Kiro CLI using Amazon Bedrock AgentCore Memory

Artificial Intelligence Extending conversational memory in Kiro CLI using Amazon Bedrock AgentCore Memory Agentic IDEs that forget what you told them in previous sessions aren’t very helpful. You work on your large codebase with complex business requirements for days or weeks. However, your IDE only remembers you during your current session and can’t recall your conversational history, preferences derived from the conversations, or additional insights. You end up providing the same contextual information in every new session. This need for repetitive context-setting impacts your productivity. In this post, we demonstrate how you can extend the conversational memory of Kiro CLI by implementing a custom Model Context Protocol (MCP) server that integrates with Amazon Bedrock AgentCore Memory. You can use Kiro CLI to interact with AI agents of Kiro directly from your terminal. Amazon Bedrock AgentCore Memory is a fully managed service that allows AI agents to retain information from past interactions, creating more intelligent and context-aware conversations. By implementing a custom MCP server, you can provide Kiro CLI with tools to store and retrieve conversation context, monitor memory usage, and manage the underlying Bedrock Agent Core Memory infrastructure. Solution overview The solution consists of three main components working together: - Amazon Bedrock AgentCore Memory is a fully managed service that stores and retrieves conversation context, providing persistent memory capabilities with built-in semantic search. AgentCore Memory provides powerful capabilities for maintaining both short-term working memory and long-term intelligent memory, so AI agents can retain context, learn from interactions, and deliver truly personalized experiences. - Custom MCP Server exposes Amazon Bedrock AgentCore Memory capabilities through the MCP, making memory operations accessible to MCP-compatible clients. - Kiro CLI connects to the MCP server through STDIO protocols to store and retrieve conversational history. The MCP server acts as a bridge between Kiro CLI and Amazon Bedrock AgentCore Memory, allowing the Kiro CLI to maintain conversation history and context across sessions.The MCP server provides tools organized into three categories. - Conversation tools – you can search conversation history by topic or timeframe, store conversations with consistent session tracking, retrieve complete conversation content, and list previously stored sessions. - Monitoring tools – you can view memory usage statistics and MCP server config - Management tools – you can delete specific sessions and delete stored data when needed. The solution uses a two-stage retrieval strategy: it first attempts semantic search using the retrieve_memory_records Bedrock AgentCore Memory API for conceptual matching, then falls back to direct event-level content matching, scanning raw conversation payloads stored in AgentCore Memory sessions. This cascading approach makes sure that conversations are retrievable regardless of whether the semantic strategy has finished processing them. You can use timeframes in your prompt like recent, last night, or yesterday to find relevant conversations. This architecture makes Kiro CLI context-aware. It remembers your preferences, project details, and workflows across sessions, so you don’t need to repeatedly provide the same information. Walkthrough For this demo, you should have the following prerequisites: - Access to an AWS account through the…