POLICY · COMPANIES · #975
Amazon Bedrock: multi-account AI agent architecture using AgentCore Gateway and MCP
Amazon’s post describes a reference architecture for building multi-account AI agents that query data in-place across multiple AWS line-of-business (LOB) accounts without centralizing datasets. It shows how a central platform account can host agents and Bedrock inference while AgentCore Gateway (with MCP, AgentCore Identity, Policy in AgentCore/Cedar, and optional Okta auth) aggregates LOB MCP servers, provides unified tool discovery, authorization, observability, and applies Bedrock guardrails and RAG-backed knowledge retrieval.
KEY POINTS
- Amazon’s post describes a reference architecture for building multi-account AI agents that query data in-place across multiple AWS line-of-business (LOB) accounts without centralizing datasets.
- It shows how a central platform account can host agents and Bedrock inference while AgentCore Gateway (with MCP, AgentCore Identity, Policy in AgentCore/Cedar, and optional Okta auth) aggregates LOB MCP servers, provides unified tool discovery, authorization, observability, and applies Bedrock guardrails and RAG-backed knowledge retrieval.
- It matters because it offers a practical pattern to let agents query cross-account data securely and govern LLM inference centrally without replicating datasets across teams.
WHY IT MATTERS
It matters because it offers a practical pattern to let agents query cross-account data securely and govern LLM inference centrally without replicating datasets across teams.