Serverless MCP server for AI agent data lake access on Amazon ECS Fargate | Amazon Web Services
Organizations building applications powered by artificial intelligence (AI) face a recurring challenge: giving large language model (LLM) agents access to enterprise data lakes without duplicating integration logic across every agent and application. Most teams begin by wiring agents directly to databases and APIs, with no shared gateway such as a Model Context Protocol (MCP) server in between. Each new dataset demands custom code, and each agent reimplements its own access control. As the number of datasets or agents grows, permission enforcement drifts, and onboarding a new data source becomes a multi-day engineering effort.
Our team supports Amazon’s North America Sort Center (NASC) network, where planning teams rely on operational data to manage capacity, labor, and package flow. To give those teams conversational access to that data, we built a serverless Model Context Protocol (MCP) server on Amazon Elastic Container Service (Amazon ECS)with AWS Fargate to address this problem for...
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