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AWS published an architecture pattern that lets a single AI agent query across multiple AWS accounts while keeping each team's data inside its own account, using Amazon Bedrock AgentCore Gateway and the MCP protocol.

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AWS Details Multi-Account AI Agent Pattern Using AgentCore Gateway and MCP

What AWS proposed

FAQ

What is AgentCore Gateway in Amazon Bedrock?

It is a component that acts as an intermediary gateway connecting an AI agent to distributed data sources and tools, handling routing and authorization instead of the agent connecting directly to each source.

What is MCP and why is it used here?

MCP (Model Context Protocol) is an open standard for connecting models and tools to external data sources. Here it is used to expose each account's data as an MCP server the agent can query.

Is this pattern useful for MENA organizations?

Yes, especially for government and banking institutions whose data-protection rules require keeping each entity's data within its own cloud boundary while still needing unified analytics.

Should teams adopt this now?

It depends on organization size and account count. If you run multiple AWS accounts and need a unified agent with data separation, it is worth evaluating, but it requires maturity in cross-account identity and permission management.

Source: AWS Machine Learning

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