Choosing a web search API for your agent
Tavily, Exa, Brave Search, Perplexity and Firecrawl each lean toward a different part of search. How to pick for your agent, and why you rarely pick just one.
2 min read
“Add web search” sounds like one decision. In practice it is several: finding sources, understanding them, reading full pages, and sometimes getting a ready answer. The search services in the Agent200 catalog each lean toward a different part of that job. Here is how to pick, and why you rarely have to pick only one.
The jobs inside “search”
- Find: return the most relevant pages for a query.
- Discover: find pages that match an idea, even when you do not know the right keywords.
- Read: turn a page into clean text or structured data the model can use.
- Answer: return a synthesized response with its sources.
The services, by the job they lean toward
Tavily
A search API built for AI agents. It returns relevant results with content already prepared for a model, which makes it a natural default for agents that need to look things up as part of a larger task.
Exa
Search by meaning. Exa is strong when the agent is exploring: finding companies like a given one, papers on a concept, or pages similar to a page it already has.
Brave Search
Results from an independent web index. A good fit when you want classic web results for a query and broad, fresh coverage.
Perplexity
An answer engine. Instead of a list of links, it returns a synthesized answer with citations. Useful when the agent needs a quick grounded answer rather than raw material.
Firecrawl
Not a search engine but a reader. Firecrawl turns a website or a page into clean, model-ready content. It pairs with any of the services above: search to find, Firecrawl to read.
A quick map
| Your agent needs to | Start with |
|---|---|
| Look up facts as part of a task | Tavily |
| Explore a topic or find similar pages | Exa |
| Get classic web results with broad coverage | Brave Search |
| Get a quick answer with citations | Perplexity |
| Read full pages or whole sites | Firecrawl |
| Reach a specific source | Wikipedia, YouTube, Reddit, X or Google Maps |
Why you rarely choose just one
Strong research agents combine them: one service to find candidates, another to read the best ones, and the model to reason over the result. Traditionally that means an account, a key and a bill per provider. Through Agent200, every one of these services is reached with your Agent200 API key and billed on one statement, so trying a second search service is a change to the tools list, not a new vendor.
Conceptual example.
tools: ["web_search", "read_page"]How to decide for your agent
- Write down the three questions your users ask most.
- Run them through two candidate services with the same model.
- Compare the answers your agent produces, not the raw results.
- Keep the combination that answers best, and revisit it as your use case grows.
See every search and data service in the integrations catalog, or read how to build a research agent.
