A lot of the teams we work with are building agents that read the web as they run. A research assistant, a live news product, a tool that watches a competitor’s pricing page. Each one is only as useful as what it can find, and the search API underneath decides most of that.
No single provider suits every case. A research agent, a news product, and a site crawler all want different things.
Which web search API should you start with?
If you want one API that can grow with the agent, Linkup is a sensible place to start. If the work is open-ended research, Exa is the one to test. If you’re only grounding an LLM with fresh context, Tavily keeps things simple. And if you already know which sites matter, Firecrawl may serve you better than another search provider.
Whichever you pick, test two of them on real queries from your product, and pay attention to the sources, how fresh they are, and how much cleanup each response needs.
Our shortlist
| Company | Choose it when | Our view |
|---|---|---|
| Linkup | You want search, research, and structured output from one API | The most complete option, and where we’d usually start |
| Exa | The query is open-ended and meaning matters more than keywords | The one to test for research and discovery |
| Tavily | You need clean, current web context for an LLM | A focused choice for simple RAG |
| Brave Search API | Index independence is part of the brief | The credible alternative to building on Google or Bing |
| Serper | You want Google results with the least ceremony | Fast and usually inexpensive |
| Firecrawl | You know the sites and need to read them whole | Built for crawling and extraction rather than search |
Details are drawn from public information and can change. Speak to each company before committing.
How the APIs compare
Linkup
For most agent products, Linkup is where we’d begin. One API gives you search, page fetching, research across several sources, structured extraction, and longer retrieval jobs. A basic search endpoint is fine for a prototype, but fairly soon the agent needs to read a page properly, compare a few sources, or hand back data in a set format. Linkup does all of that without you having to stitch three providers together. It also holds up on the enterprise side. It’s SOC 2 Type II certified, and you can get zero data retention, SSO, bring your own cloud, and private VPC deployment.
Exa
Exa suits open-ended questions. It searches by meaning rather than just the words you type, so it’s good at finding research papers, niche sources, and pages that talk about the right idea in different language. A normal keyword search misses a lot of that. If your product is about research or discovery, it’s worth a test.
Tavily
Tavily pulls in current web content in a form an LLM can use straight away, and it works with the frameworks most AI teams already use. It’s not built for deep crawling or a wide range of retrieval jobs. For plain RAG, it does the job well.
Brave Search API
Brave runs its own web index. That means you’re not building on Google or Bing, which matters if privacy, control, or a different set of results is part of what you need.
Serper
Sometimes you just want Google results through an API. Serper gives you that, and it’s fast, simple, and usually cheap at volume. You get Google’s results and not much control over how they’re put together, which is fine if that’s all you need.
Firecrawl
Firecrawl is a bit different from the others. It doesn’t choose which page matters. You give it a page, and it reads it, follows the rest of the site, and returns clean or structured content. That makes it good for pulling in whole sites, monitoring them, and large extraction jobs. It also pairs well with a search API.
How to run a fair test
Take Linkup and one of the others that fits your job, and run both on real queries from your product for a week. Keep the one that leaves your agent the least work to do after the search.
