aws-knowledge
Overview
The aws-knowledge MCP server is a Model Context Protocol (MCP) server that gives AI assistants structured access to curated AWS knowledge sources, including architectural guidance, best practices, service concepts, and operational recommendations. It’s designed to help AI workflows answer how and why questions about AWS — not just API mechanics — by grounding responses in authoritative AWS knowledge rather than raw documentation alone.
Transport
streamable-http
Tools
Key Capabilities
- Architectural guidance access — Retrieve AWS best practices, design principles, and solution guidance programmatically.
- Concept-level reasoning support — Go beyond API docs to answer questions about tradeoffs, patterns, and recommended approaches.
- Contextual discovery — Surface related knowledge to help agents explore topics deeply and holistically.
- Grounded AI responses — Reduce hallucinations by anchoring answers in vetted AWS knowledge sources.
How It Works
The aws-knowledge MCP server runs as a local or containerized MCP service and listens for requests from AI clients over standard MCP transports. When an agent invokes a tool like search_knowledge, the server queries AWS-curated knowledge sources and returns structured results that the assistant can reason over or summarize.
When deeper detail is needed, tools such as read_knowledge_item fetch the full content of a specific knowledge entry, formatted for direct use in AI workflows. Recommendation tools help agents expand their understanding by suggesting related patterns, best practices, or conceptual guidance.
By separating knowledge retrieval from raw documentation access, this server allows AI assistants to provide higher-level AWS guidance — such as architectural recommendations, operational considerations, and best-practice explanations — without requiring the user to manually search whitepapers or reference material.