Connect an AgentCore Runtime hosted MCP server to Amazon Quick

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Model Context Protocol (MCP) servers allow foundation models to access external data and tools, supporting standardized, secure access to files, databases, and APIs. They give AI agents the ability to interact with real-world applications, reduce hallucinations with accurate context, and offer stateful, multi-turn capabilities. Industry-standard architectures quickly evolved and adopted MCP to power agentic AI workflows. Amazon Quick supports MCP integrations for autonomous execution, real-time data access, and specialized AI sub-agent integrations. If you already have an MCP server, you can use this integration guide to integrate it with Amazon Quick. If you do not have an MCP server yet, you can use the AWS provided guidance for deploying MCP servers on AWS, which follows AWS Well-Architected pillars. Depending on your use case, you have several options: If you have your own REST API or one running on Amazon API Gateway, you can integrate Amazon Quick directly with your API using Amazon Bedrock AgentCore Gateway. If you prefer a serverless architecture and need only the bare minimum execution capability for your AI agent, you can author an AWS Lambda function and integrate with Amazon Quick using AgentCore Gateway. If you want a fully managed serverless MCP server solution with session isolation, extended execution time, persistent file systems, built-in authentication, observability, enhanced payload, bidirectional streaming, and evaluations, you can use AgentCore Runtime for MCP server hosting and connect with Amazon Quick using AgentCore Gateway. In this …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen: Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://aws.amazon.com/blogs/machine-learning/connect-an-agentcore-runtime-hosted-mcp-server-to-amazon-quick/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.