Before MCP, LLMs relied on ad-hoc, model-specific integrations to access external tools. Approaches like ReAct interleave chain-of-thought reasoning with explicit function calls, while Toolformer trains the model to learn when and…
Before MCP, LLMs relied on ad-hoc, model-specific integrations to access external tools. Approaches like ReAct interleave chain-of-thought reasoning with explicit function calls, while Toolformer trains the model to learn when and…