Infragistics Blog - #Model Context Protocol

MCP vs RAG is the central tradeoff this report measures: retrieval-augmented generation over a static vector index is the default architecture for AI documentation assistants, but it degrades silently as source documentation changes faster than the index is rebuilt. This report benchmarks that architecture against a Model Context Protocol (MCP) server that queries Ignite UI documentation and API definitions, using Anthropic Claude as the orchestrating model in both configurations.

MCP vs RAG: MCP-based retrieval beats a vector-indexed RAG on grounding and citation depth, but it's slower and more expensive. Use it for correctness-critical requests; keep RAG for high-volume, latency-sensitive ones.

AI results improve over time even when the model never changes - context accumulation across your dev stack. Run a clean-room test to measure your true baseline.