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The AWS team built a serverless MCP server on Amazon ECS Fargate as a centralized gateway for AI agents to access the enterprise data lake. The architecture is divided into four layers: client, MCP server, tools, and knowledge base refresh. Agents powered by Amazon Bedrock orchestrate FastMCP tools and query data through Athena, Redshift, and Bedrock Knowledge Bases. Adding a new dataset requires only a single JSON metadata file, with no integration code needed. In testing, context mapping kept end-to-end interaction latency at 15–20 seconds.
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AWS builds a serverless MCP server on Amazon ECS Fargate to provide data lake access for AI agentsDevelopments
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- Source:AWS Machine Learning
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Nov 7
AWS Machine LearningFirst-party
AWS builds a serverless MCP server on Amazon ECS Fargate to provide data lake access for AI agents
The AWS team built a serverless MCP server on Amazon ECS Fargate as a centralized gateway for AI agents to access the enterprise data lake; adding a new dataset requires only a single JSON metadata file, with no integration code needed. The architecture is divided into four layers: client, MCP server, tools, and knowledge base refresh. Agents powered by Amazon Bedrock orchestrate FastMCP tools and query data through Athena, Redshift, and Bedrock Knowledge Bases. In testing, context mapping kept end-to-end interaction latency at 15–20 seconds.