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*   [Use cases](/v0.1/docs/use_cases/)
*   Tool use

Tool use
========

An exciting use case for LLMs is building natural language interfaces for other "tools", whether those are APIs, functions, databases, etc. LangChain is great for building such interfaces because it has:

*   Good model output parsing, which makes it easy to extract JSON, XML, OpenAI function-calls, etc. from model outputs.
*   A large collection of built-in [Tools](/v0.1/docs/integrations/tools/).
*   Provides a lot of flexibility in how you call these tools.

There are two main ways to use tools: [chains](/v0.1/docs/modules/chains/) and [agents](/v0.1/docs/modules/agents/). Chains lets you create a pre-defined sequence of tool usage(s). Agents let the model use tools in a loop, so that it can decide how many times to use tools.

To get started with both approaches, head to the [Quickstart](/v0.1/docs/use_cases/tool_use/quickstart/) page.

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