LLM function calls are inefficient for handling large data outputs from MCP tools, as they require excessive token usage and can lead to inaccuracies. A more effective approach is to use structured data with output schemas and code orchestration to simplify data processing and improve scalability. This shift may enable better performance in real-world applications involving large datasets.