Amazon Quick is Amazon’s agentic AI companion built for work. You build agents that reason over your data, call action connectors, and carry multi-step tasks to completion. Promoting those resources (chat agents, action connectors, knowledge bases, flows, and spaces) from a development to a production AWS account, the way you would any other application, has been a manual and error-prone chore. This post shows how to automate it with an idempotent, auditable Model Context Protocol (MCP) server on Amazon Bedrock AgentCore.

The building blocks of an agentic solution are its agents, action connectors, knowledge bases, and spaces: chat agents configured with custom instructions, connectors for Slack, Jira, and other integrations, knowledge bases grounded in your own documents, and the Space that binds them together. Teams assemble and iterate on them quickly in a development account.

Most enterprises run separate AWS accounts for development and production, sometimes with quality assurance (QA) in between. When agents, action connectors, and knowledge bases are validated in a development account, there is no native, one-click way to promote them into the next account. Teams rebuild each resource by hand: recreate each agent with the same instructions and starter prompts, re-attach each agent’s action connectors, re-grant resource permissions, and reprovision the Amazon Simple Storage Service (Amazon S3) bucket, bucket policy, and data source behind each knowledge base. The work is slow, difficult to audit, and easy to get subtly wrong, which undermines the governance story enterprises need.