AI Search APIs for Agents: How Tavily, Exa, Brave, and the Rest Stack Up

A new category of search

If you are building an AI agent that needs to read the web, you face a choice that did not exist a few years ago. On one side sit traditional SERP APIs such as Serper.dev and SerpApi, which hand back raw Google-style metadata—titles, URLs, and snippets—and leave you to build your own extraction layer. On the other side are AI-native search APIs like Tavily, Exa, Perplexity, Linkup, and Firecrawl, which return content already cleaned and structured for large language models [9][2].

The ground shifted hard in 2025. Microsoft retired the Bing Search API, disabling new resources in February and returning HTTP 410 on the public endpoints by August 11, 2025; its recommended replacement, Grounding with Bing Search in Azure AI Foundry, is a platform commitment rather than a drop-in API [33]. Brave reports that Google also took legal action against SerpApi late in 2025, narrowing the field of independent, at-scale Western indexes to roughly three: Brave, Google, and Bing [21]. The result is a fast-moving market—so treat any single benchmark or free-tier figure as a snapshot, especially since many comparisons come from vendor blogs that crown their own product.

Tavily: the bundled reference point

Tavily positions itself as a "web infrastructure layer for AI agents," combining search with Extract, Map, and Crawl, and emitting citation-ready snippets, markdown, or plain text [4]. Its free tier is generous: 1,000 credits per month, no credit card required, and free for students. Pay-as-you-go runs $0.008 per credit, with a basic search costing 1 credit and an advanced search 2 [4]. Official LangChain, LlamaIndex, and MCP integrations make it easy to wire into agent stacks [4].

The pros are predictable, operation-specific pricing and end-to-end content acquisition in one platform. The cons: it is search-first, so deep structured extraction or full-site crawling may need a partner tool, and critics flag an "extraction noise" tax where nav and footer junk consumes tokens, plus occasional stale links [21]. Note that Tavily was acquired by Nebius in February 2026, with the team reportedly intact [12]. Best at: RAG prototyping and agent pipelines that want bundled search plus extraction with steady costs.

Exa: semantic discovery

Exa is an AI-first neural engine built on embeddings trained for link prediction, with a distinctive "Find Similar" feature and Websets [10][13]. After a March 2026 simplification, search-with-contents costs $7 per 1,000 requests, with Exa Deep at $12 and a reasoning variant at $15 [11]. Its free tier is murky—sources cite either roughly 1,000 trial credits or no public free tier [2][12]. Exa earns the highest quality score (3.82/5) in one benchmark but trails on raw keyword fidelity and rate limits (~5–10 requests/second) [10][8]. Best at: semantic research, finding conceptually similar pages, and meaning-over-keywords RAG.

Brave: independent and fast

Brave's API draws on its own index of 30–35 billion-plus pages and added an LLM Context API in February 2026 [20][21]. It is the fastest in independent benchmarks at 669 ms and offers strong privacy credentials (SOC 2 Type II, zero data retention) [8][20]. Search is $5 per 1,000 requests [24]. The catch: the standalone free tier was removed for new users in late 2025/early 2026, replaced by $5/month in renewing credits (~1,000 queries), while existing free-plan users keep 2,000/month [22]. Its index is smaller than Google's, and it returns SERP-style JSON, so RAG pipelines need a separate extraction step [21]. Best at: privacy-sensitive, latency-critical, or high-volume deployments where search is a supporting feature.

Serper.dev: cheap Google fidelity

Serper bills itself as the fastest and cheapest Google Search API, with 2,500 free queries on signup and credits as low as $0.30 per 1,000 at scale, plus rate limits up to 300 QPS [27][15]. It returns genuine Google results but offers no content extraction or semantic understanding, and queries returning more than 10 results cost double [16]. Best at: cheap, high-fidelity Google SERP data at volume when you own the extraction layer.

Perplexity Sonar: cited answers

Perplexity's Sonar API folds search, synthesis, and inline citations into one call—hard to replicate yourself [1]. There is no standard free tier, though Pro subscribers get $5/month in API credit and new accounts may get trial credits [26]. The trade-offs are real: benchmarks show ~11-second latency, it is rate-limited by design, and Reddit users have complained about hidden citation-token costs [8][30]. Best at: end-user research and answer products that can tolerate async, deep-research workloads.

Linkup and Firecrawl: accuracy and extraction

Linkup, a French API focused on verified facts from trusted and premium sources, offers €5/month in queries (~1,000 standard) and claims the top spot on OpenAI's SimpleQA factuality benchmark—Deep Search around 90.1% [2]. It lacks neural "Find Similar" and has a smaller developer community. Best at: business intelligence and fact-checking where source trust matters most.

Firecrawl unifies Search, Scrape, Crawl, and Map under one API with clean markdown, a 1,000-credit free tier, and SOC 2 Type 2 compliance [9][31]. It has no semantic search and no pure pay-per-use plan, but it shines on full-page retrieval. Best at: workflows that need search plus structured extraction together.

Choosing well

No single tool wins outright—benchmark quality gaps among the top tier are described as not statistically significant [8]. Pick by task: Serper for cheap Google data, Brave for speed and privacy, Exa for semantic discovery, Tavily or Firecrawl for RAG ingestion, Linkup for factual accuracy, and Perplexity for synthesized cited answers.