AWS published a reference architecture implementing an 'Adjudicated Query' pattern: Amazon Quick's chat agent translates natural-language compliance questions into calls on a bounded MCP tool surface, while a deterministic rules engine makes all pass/fail decisions. The design targets sweeping tens of thousands of leases against changing state landlord-tenant laws while provably accounting for every record. A deployable CDK sample with synthetic data ships on GitHub.
Smartsheet built a remote Model Context Protocol (MCP) server on AWS, enabling AI assistants like Amazon Quick and Claude Desktop to directly access Smartsheet's enterprise work management data. This bridges the gap between AI agents and structured data in enterprise systems.
Smartsheet built a remote Model Context Protocol (MCP) server on AWS, enabling AI assistants like Amazon Quick and Claude Desktop to directly access Smartsheet's enterprise work management data. This bridges the gap between AI agents and structured data in enterprise systems.
An AWS post outlines best practices for Amazon Quick Automate, a multi-agent automation capability within Amazon Quick. It helps enterprises deploy agents that reason over context and coordinate across departments, systems, UIs, APIs, and third-party applications instead of following rigid scripts.
An AWS post outlines best practices for Amazon Quick Automate, a multi-agent automation capability within Amazon Quick. It helps enterprises deploy agents that reason over context and coordinate across departments, systems, UIs, APIs, and third-party applications instead of following rigid scripts.
AWS is converging computer vision, Strands Agents, and the Model Context Protocol (MCP) to enable visual intelligence applications on Amazon Bedrock. This integration aims to bridge the gap between systems that see, think, and act, reducing the complexity of managing multiple APIs and custom integrations.
AWS is converging computer vision, Strands Agents, and the Model Context Protocol (MCP) to enable visual intelligence applications on Amazon Bedrock. This integration aims to bridge the gap between systems that see, think, and act, reducing the complexity of managing multiple APIs and custom integrations.
An AWS guide walks through connecting MCP servers hosted on AgentCore Runtime to Amazon Quick, letting foundation models access external data and tools through standardized, secure integrations. The post frames MCP as the emerging standard for agentic AI workflows, enabling stateful, multi-turn agent capabilities with reduced hallucination via accurate context.
An AWS guide walks through connecting MCP servers hosted on AgentCore Runtime to Amazon Quick, letting foundation models access external data and tools through standardized, secure integrations. The post frames MCP as the emerging standard for agentic AI workflows, enabling stateful, multi-turn agent capabilities with reduced hallucination via accurate context.
Amazon Quick's Live Data in Apps lets AI-built Quick apps query governed Quick Sight datasets live at view time instead of relying on build-time snapshots. Queries run as the viewing user, so row-level and column-level security apply per person, with server-side consent enforced on every query. This matters for practitioners because it removes manual data refresh and snapshot management from no-code, natural-language app building.
Amazon Quick's Live Data in Apps lets AI-built Quick apps query governed Quick Sight datasets live at view time instead of relying on build-time snapshots. Queries run as the viewing user, so row-level and column-level security apply per person, with server-side consent enforced on every query. This matters for practitioners because it removes manual data refresh and snapshot management from no-code, natural-language app building.