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How Eon built multi-cloud investigation with an MCP Gateway on Amazon Bedrock AgentCore

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How Eon built multi-cloud investigation with an MCP Gateway on Amazon Bedrock AgentCore

Independent software vendors (ISVs) building AI-powered products need to connect agents and humans to dozens of operational tools across clouds, each with different authentication models, network boundaries, and access policies. When those tools span AWS, GCP, and Azure simultaneously, the integration surface multiplies.

This post describes how Eon used Amazon Bedrock AgentCore, a platform to build, connect, and optimize agents at scale, with any framework or model. Eon used it to replace per-tool credentials and local Model Context Protocol (MCP) processes with a single authenticated gateway. The result gives developers and autonomous agents unified access to investigation tooling across three clouds. New engineers now reach all their investigation tools in about two minutes instead of the two days it previously took to configure credentials and local MCP servers.

Eon provides the Autonomous Data Foundation for the AI era. The platform discovers and classifies cloud resources across AWS, Azure, and GCP. It provides continuous deduplicated backup that reduces storage costs by up to 50 percent in Eon’s internal measurements. It also detects ransomware and rogue-agent damage and delivers live grounded context for AI agents. All of this runs from a single read-only AWS Identity and Access Management (IAM) role, storing data in Apache Parquet and Apache Iceberg formats. Founded by former AWS engineers, Eon runs its software as a service (SaaS) infrastructure on AWS.

Eon’s internal engineering team investigates production incidents across multiple clouds and dozens of operational systems. A crashed Kubernetes pod requires checking container logs, Grafana metrics, the deployment’s GitHub pull request (PR), and cloud-provider health status within the same session.


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