Search API designed specifically for LLM and agent use.
An AI-optimized search API — gives your AI agent clean, relevant search results instead of raw web pages.
Tavily is an AI-native search API designed specifically for LLM applications and AI agents. Unlike traditional search APIs that return a list of URLs, Tavily performs the search, reads and extracts content from the most relevant pages, and returns synthesized, LLM-ready content. This "search and extract" approach means agents get usable information in a single API call rather than needing separate search and scraping steps.
The core API accepts a search query and returns results with extracted content, relevance scores, and source URLs. Tavily's search algorithm is optimized for factual accuracy and comprehensiveness rather than SEO rankings, which often produces more relevant results for agent research tasks than Google-based search APIs. The API supports parameters for search depth (basic vs. comprehensive), topic categories (general, news, finance), domain inclusion/exclusion, and maximum results.
Tavily's "extract" endpoint goes further: given a list of URLs, it extracts and returns the main content of each page in clean text format, handling JavaScript rendering, paywalls (where possible), and content extraction automatically. This eliminates the need for separate scraping tools in many agent workflows. The combined search-and-extract capability is particularly valuable for research agents that need to synthesize information from multiple sources.
Integration with agent frameworks is extensive. Tavily is the default search tool in LangChain's agent templates and is prominently featured in LangGraph's ReAct agent examples. It's also integrated with CrewAI, AutoGen, and LlamaIndex. OpenAI's function calling documentation frequently uses Tavily as the example search tool implementation. This positioning as the AI-native search standard has given Tavily strong adoption in the agent developer community.
The free tier provides 1,000 API calls per month, with paid plans starting at $80/month for 12,000 calls. Pricing is higher than simple search APIs like Serper because Tavily includes content extraction in each call. For agents that would otherwise need both search and scraping tools, the combined cost is often competitive.
Limitations include slower response times compared to simple search APIs (3-5 seconds for comprehensive searches due to content extraction), occasional extraction failures on heavily JavaScript-dependent sites, and less control over the exact search engine used. Tavily is best suited for research-focused agents that need synthesized, ready-to-use content rather than raw search result links.
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Tavily leads the AI-native search category with built-in content extraction that eliminates the search-then-scrape pattern. Higher priced than simple search APIs but the time savings from integrated extraction justify the cost for research agents.
AI-powered search that understands natural language queries and returns relevant results ranked by meaning.
Use Case:
Building intelligent search experiences that understand user intent rather than just matching keywords.
Real-time web search capabilities that agents can use to find current information and verify facts.
Use Case:
Grounding AI agent responses in current, factual information from the live web to reduce hallucinations.
Query structured and unstructured knowledge bases with natural language and get contextually relevant results.
Use Case:
RAG applications that need to search across internal documents, wikis, and knowledge bases.
Search across multiple data sources simultaneously with unified ranking and deduplication.
Use Case:
Comprehensive search experiences that combine results from internal databases, documents, and external sources.
Fine-tune search relevance with custom ranking models, boosting rules, and business logic filters.
Use Case:
Tailoring search results to specific use cases with domain-specific relevance tuning.
Simple API with client libraries, comprehensive documentation, and generous free tiers for development.
Use Case:
Quickly integrating search capabilities into AI agents and applications with minimal setup.
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View Pricing Options →Automating multi-step business workflows with LLM decision layers.
Building retrieval-augmented assistants for internal knowledge.
Creating production-grade tool-using agents with controls.
Accelerating prototyping while preserving deployment discipline.
Tavily works with these platforms and services:
We believe in transparent reviews. Here's what Tavily doesn't handle well:
Tavily provides reliable API responses with built-in content extraction, though comprehensive search mode takes 3-5 seconds due to page reading. The API returns structured results with relevance scores, source URLs, and extracted content. Rate limits depend on plan tier. For production resilience, implement timeout handling (comprehensive searches can be slow), cache results for repeated queries, and have a fallback search provider for when extraction fails on specific pages.
No, Tavily is a cloud-hosted API service with no self-hosted option. The search and content extraction pipeline runs on Tavily's infrastructure. For self-hosted alternatives that combine search and extraction, consider running SearXNG for search combined with Firecrawl's open-source version for content extraction, though this requires managing two separate services.
Tavily charges per API call with plans starting at $80/month for 12,000 calls. Optimize by using 'basic' search depth instead of 'comprehensive' when full content extraction isn't needed, caching results for repeated queries, limiting max_results to only what your agent needs, and using domain filtering to focus searches on high-quality sources. The free tier of 1,000 calls/month is sufficient for development.
Tavily's API is purpose-built for AI applications with a unique search-and-extract approach. Migration to other search APIs (Serper, Brave) would lose the integrated content extraction — you'd need to add a separate scraping step. LangChain provides a TavilySearchResults tool that abstracts the API, making provider swaps possible at the framework level. The main lock-in is the convenience of combined search and extraction in a single call.
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In 2026, Tavily launched enhanced search depth options with comprehensive mode for thorough research, added domain-specific search categories for news and finance, and improved content extraction quality with better handling of JavaScript-rendered pages.
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