# What Is Function Calling?

> Function calling is the structured interface that lets LLMs invoke external functions with typed parameters — the technical foundation of agent tool use.

**Term:** Function Calling  
**Category:** Capabilities  
**Also known as:** tool calling, structured tool invocation  
**Updated:** 2026-07-22  
**Canonical:** https://www.frameworkr.com/glossary/function-calling

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**Function calling** is the mechanism by which a large language model invokes external functions with structured, typed parameters instead of generating free-form text.

When a model "calls a function," it outputs a JSON object specifying the function name and arguments. Your application executes the function and feeds the result back into the model's context for the next reasoning step.

## Function calling vs. tool use

The terms are often used interchangeably. In practice:

- **Function calling** describes the API-level capability (OpenAI, Anthropic, Google all support it)
- **Tool use** describes the agent-level pattern of selecting and invoking capabilities to achieve goals

Function calling is the plumbing. Tool use is the architecture.

## Schema design matters

Models choose tools based on name and description. A function defined as `query_db(sql: string)` will be misused. One defined as `get_tenant_maintenance_history(unit_id: string, limit: number)` gives the model enough context to call it correctly.

Parameter schemas should be explicit, validated, and as narrow as possible.

## Related reading

See [Tool Use](/glossary/tool-use) for how function calling fits into the broader agent architecture.

## Related terms

- [tool use](https://www.frameworkr.com/glossary/tool-use.md)
- [ai agent](https://www.frameworkr.com/glossary/ai-agent.md)
- [model context protocol](https://www.frameworkr.com/glossary/model-context-protocol.md)


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_Published by Frameworkr — https://www.frameworkr.com_