> ## 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.

# Google Scholar and patent search for AI agents

> Google Scholar and Google Patents results by keyword through Serper, with country, language, recency and paging — plus where to go for arXiv and AMiner.

Literature and prior-art questions come up in research, due diligence and
product work alike, and both need an index that is current. Through AgentKey
your agent searches Google Scholar and Google Patents results through Serper
with the same three calls — `find_tools`, `describe_tool`, `execute_tool` —
and can follow a hit into the [Academic](/capabilities/academic/papers)
category for arXiv and AMiner paper records.

## What you can ask

* *"Search Google Scholar for 'protein language model' papers from the past year."*
* *"Find scholarly articles on graph neural networks for traffic forecasting, second page."*
* *"Which patents mention 'solid-state battery electrolyte'? List titles and links."*
* *"Are there patents on foldable display hinges that name Samsung?"*
* *"Give me 20 Scholar results for 'LLM evaluation benchmark' with a Chinese interface."*
* *"Find prior art for a drone package-delivery latch published in the past year."*
* *"Find the arXiv version of this paper and its abstract."*

## What's covered

**Scholarly literature**

* Keyword search over Google Scholar results — articles, theses, books and
  preprints as Scholar indexes them
* A country code, interface language and free-text location to bias results
* A time filter — past hour, day, week, month or year — plus result count and
  page numbers
* Autocorrect on by default, switchable

**Patents**

* Keyword search over Google Patents results
* The same country, language, location, time-filter, count and paging
  controls

**Beyond Google**

* Paper search and paper detail with normalized records from arXiv and
  AMiner, plus researcher and institution lookups, live in
  [Academic](/capabilities/academic/papers)

## How to use it

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

```text theme={null}
find_tools(q="Google Scholar results for protein language models from the past year")
find_tools(q="patents mentioning solid-state battery electrolyte")
find_tools(prefix="search/serper")        # scholar and patent search
describe_tool("<returned Provider/Operation>")
execute_tool("<Provider/Operation>", { ...params })
```

Always `describe_tool` before executing — recency is the `tbs` filter, paging
is `page`, and the result fields differ between Scholar and Patents.

> [!NOTE]
>
> **Building with code?** Scholar results are one of the engines behind the
> fixed-contract
> [`academic.paper.search`](/api-reference/scenario/methods/academic-paper-search)
> Scenario Method, which returns a normalized paper page with automatic
> provider failover; see [Scenario Methods](/api-reference/scenario/overview).
> Patent search is available through the catalog tool above.

## FAQ

> **Do I get the full paper or patent text?**
>
> No. Results carry the title, link and snippet as Google returns them. To
> read a PDF or a patent page, pass the link to a
> [scrape tool](/capabilities/scrape/url-to-markdown); Firecrawl parses PDFs
> into markdown.

> **Which regions and languages?**
>
> Any Google country code and interface language, plus a free-text location.
> Queries can be written in any language.

> **How fresh are the results?**
>
> Fetched from Google at request time. The time filter narrows by Google's
> own indexing date.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.