Function Calling
Also known as: Tool use, Tool calling
The model emits structured JSON specifying a tool call instead of free text; the host executes it.
An LLM capability where the model outputs structured JSON specifying which tool/API to call with what arguments, rather than free-form text. The host application then executes the call and feeds the result back into the conversation.
In practice
Foundational to every agent system. Expect questions on schema design, parallel tool calls, and error recovery.
How it compares
Function calling is the model behavior; MCP is one standard protocol for how tools are described and invoked.
Comparisons that include Function Calling
Related topics
Questions that mention this term
Related terms
Prompt Engineering
Crafting the input text so the model produces the behavior you want.
AI Agents
LLMs that loop: plan → call tools → observe results → repeat until done.
Model Context Protocol (MCP)
An open protocol (from Anthropic) for letting LLMs call tools and read resources from any compatible server.
Chain-of-Thought (CoT)
Ask the model to think step by step before answering. It boosts accuracy on reasoning tasks.
In-Context Learning (ICL)
Show the model a few examples in the prompt and it learns the pattern, no fine-tuning needed.
Prompt Injection
Attacker text in user input or retrieved content overrides the model's system prompt or hijacks tool calls.