Enhance generative AI solutions using Amazon Q index with Model Context Protocol – Part 1

Today’s enterprises increasingly rely on AI-driven applications to enhance decision-making, streamline workflows, and deliver improved customer experiences. Achieving these outcomes demands secure, timely, and accurate access to authoritative data—especially when such data resides across diverse repositories and applications within strict enterprise security boundaries.

Interoperable technologies powered by open standards like the Model Context Protocol (MCP) are rapidly emerging. MCP simplifies the process for connecting AI applications and agents to third-party tools and data sources, enabling lightweight, real-time interactions and structured operations with minimal engineering effort. Independent software vendor (ISV) applications can securely query their customers’ Amazon Q index using cross-account access, retrieving only the content each user is authorized to see, such as documents, tickets, chat threads, CRM records, and more. Amazon Q connectors regularly sync and index this data to keep it fresh. Amazon Q index’s hybrid semantic-plus-keyword ranking then helps ISVs deliver context-rich answers without ...