Research agents and search APIs

A research agent turns a question into a plan, runs many searches, reads the pages or papers it finds, and writes up an answer with citations. A plain chat answer draws on what a model already knows and maybe one quick search. A research agent spends several minutes, sometimes longer, gathering and reading sources before it writes.

This category also includes the search APIs that agents call. When you build your own agent, it needs a way to search the web and read pages in a form a model can use. Search APIs built for agents return cleaned text and short snippets instead of a page of ads and links, and some can fetch the full content of a result in the same call.

Research agents save time on the first pass: finding what has been written on a topic, pulling together scattered sources and producing a draft that a person can check. They are less reliable at judging which sources are trustworthy, noticing when evidence conflicts, or knowing when a question has no good answer yet. A report can read well and still rest on a weak or outdated source.

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5 AI agent tools in research agents and search apis

Gemini Deep Research

by Google

Feature in the Gemini app that plans a search, reads many web pages and writes a cited report on your question.

ChatGPT deep research

by OpenAI

ChatGPT mode that browses and reads sources for several minutes, then returns a long report with citations.

Undermind

Research agent for scientific literature that searches papers step by step and explains which ones match your question.

Exa

Search engine API built for AI apps, returning links and page contents that agents can read directly.

  • Developer API

Tavily

Web search and extraction API made for agents, returning short cleaned results instead of a page of links.

  • Developer API

Check the citations, not just the summary. Open the sources behind the claims that matter most and confirm they say what the report says. For academic work, tools that search scholarly databases are a better fit than general web research, because they read papers rather than blog posts about papers.

If you are choosing a search API, test it with the kinds of questions your agent will actually ask. Compare how fresh the results are, how well it handles narrow technical queries, whether it returns full page text, and how it reports where content came from.

For teams, decide where research output goes and who checks it. A report that lands in a shared drive with no reviewer tends to be quoted later as if it were verified. Keep the original question, the date of the run and the source list with each report, so a reader can judge how current it is and rerun it when the topic moves. If the research touches confidential plans or customer data, check what the tool sends to outside search engines, since your queries themselves can reveal what you are working on.

Questions about research agents and search apis

How long does a deep research run take?

Usually several minutes, depending on the tool and the question. The agent runs many searches and reads many pages before writing, which is why it is slower than a normal chat answer.

Can I trust the citations in a research report?

Treat them as leads to check. Agents sometimes cite a source that only partly supports a claim, or rely on an outdated page. Open the sources behind the most important claims before you repeat them.

What is a search API for agents?

It is a web search service designed to be called by software rather than people. It returns results in a clean, structured form, often with page text included, so an agent can read sources without scraping web pages itself.

Are research agents good for academic literature reviews?

Tools built for scholarly search are a better starting point than general web agents, since they search papers directly. Even then, use the results to find papers to read, and do not treat the summary as a review.

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