> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentkey.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Answer engines and LLM context for AI agents

> Grounded answers and model-ready web context from Perplexity, Brave's LLM context and summarizer, and Tavily's answers, extract, crawl and map.

Sometimes an agent does not want ten blue links — it wants the answer, or it
wants the relevant passages already cut to fit its context window. Through
AgentKey your agent gets both with the same three calls — `find_tools`,
`describe_tool`, `execute_tool` — from Perplexity's search with page
contents, Brave's LLM-context chunks and summarizer, and Tavily's generated
answers, URL extraction, site crawl and site map.

## What you can ask

* *"Answer with citations: what changed in Python 3.14's free-threading support?"*
* *"Give me about 8,000 tokens of grounded web context on the EU Digital Markets Act, from the last month."*
* *"Pull the page contents for the top results on 'Rust async cancellation safety', capped at 4,000 tokens per page."*
* *"Extract these three URLs as markdown and rank the passages by relevance to 'pricing changes'."*
* *"Only use docs.python.org and peps.python.org as sources."*
* *"Summarize what the web says about this startup, with the source URLs."*
* *"Map the structure of docs.example.com, then crawl the API section."*

## What's covered

**Direct answers**

* A grounded answer to a question with optional citations and entity
  metadata, in a chosen country backend and language, from Brave
* A quick or more detailed generated answer returned alongside Tavily search
  results
* A summary of the web results for a query from Brave's summarizer, requested
  as part of a web search

**Context shaped for a model**

* Brave LLM context: web-content chunks with budgets for the number of URLs,
  snippets per URL, tokens per URL and total tokens; a strict, lenient or
  balanced relevance threshold; freshness, country and language; optional
  source metadata and local results
* Perplexity search with relevant page contents: result count, total and
  per-page token limits, country, language filters, a domain allow-list,
  recency from the past hour to the past year, and publish or last-updated
  date windows
* Tavily search with each page's cleaned content as markdown or text, and
  relevance-ranked chunks per source at advanced depth

**Content from URLs you already have**

* Tavily extract: one or more URLs returned as markdown or plain text, at
  basic or advanced depth for tables and embedded content, optionally with
  images and with passages re-ranked against a query
* Tavily crawl: traverse a site from a base URL, exploring many paths in
  parallel with built-in extraction
* Tavily map: the structure of a site from a base URL

## How to use it

Pass the request in plain language and let the router pick the tool:

```text theme={null}
find_tools(q="answer with sources: what changed in Python 3.14 free-threading")
find_tools(q="web context chunks about the EU Digital Markets Act for my prompt")
find_tools(prefix="search/perplexity")
find_tools(prefix="search/brave")         # LLM context, summarizer
find_tools(prefix="search/tavily")        # answers, extract, crawl, map
describe_tool("<returned Provider/Operation>")
execute_tool("<Provider/Operation>", { ...params })
```

Always `describe_tool` before executing — Tavily's answer rides on its
search call, Brave's LLM context takes a query with token budgets, Perplexity
takes `max_tokens` and `max_tokens_per_page`, and per-call costs differ.

> [!NOTE]
>
> **Building with code?** The same capability is available as a fixed-contract
> [Scenario Method](/api-reference/scenario/overview) with automatic provider
> failover: [`web.answer`](/api-reference/scenario/methods/web-answer) answers
> a question from live web search results and returns the sources the answer
> was grounded in. For a single page's text use
> [`web.scrape`](/api-reference/scenario/methods/web-scrape).

## FAQ

> **Are the answers grounded?**
>
> Yes — every answer tool here searches the live web first and returns the
> sources it used, so your agent can cite or verify them. Treat the answer
> text as a draft and the sources as the evidence.

> **How fresh is the context?**
>
> Fetched at request time. Brave and Perplexity accept freshness or recency
> filters; Perplexity also filters by publish and last-updated dates.

> **Which languages and regions?**
>
> Brave's LLM context takes a country and a language; Perplexity takes a
> country and ISO 639-1 language codes; Tavily is scoped by domain lists.
> Questions can be asked in any language.


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