선언형 MCP, AI 코딩 에이전트의 컨텍스트 문제를 풀다

MCP has become essential infrastructure for addressing AI-assisted coding's core challenges—96% of developers distrust AI-generated code due to insufficient context and frequent inaccuracies. By enabling agents to dynamically retrieve relevant data, documentation, and system context at runtime, MCP allows precise, lightweight prompts that dramatically improve accuracy while reducing hallucinations. This shift from static context injection to real-time, demand-driven retrieval fundamentally changes how teams can trust and scale agentic development practices.