Tavily

Tavily is a search engine built for AI agents and large language model applications. It provides one API for real-time web access, with endpoints to search the web, extract content from pages, crawl sites and run research tasks. Results come back structured and split into chunks suited to models, so an agent can reason over current information rather than relying only on its training data. Tavily is also known for its connection to the open-source GPT Researcher project. The company says more than three million developers use it.

Features

Search returns relevant sources and content chunks for a query, with options for search depth, maximum results and an included answer. Extract pulls clean content from specific URLs, and crawl follows links across a site. Tavily describes a production retrieval stack with caching and indexing designed to keep latency predictable as traffic grows.

Safeguards

Requests pass through security, privacy and content validation layers. The homepage shows an example in which a query containing an email address is blocked because personal data was detected. Tavily says these layers also guard against prompt injection and malicious sources, which is an important concern when agents read untrusted web pages.

Pricing

The free Researcher plan includes 1,000 API credits per month with no credit card required. Pay As You Go costs $0.008 per credit. The Project plan starts at $30 per month for 4,000 credits with higher rate limits, and can be scaled with a slider. Enterprise plans offer custom volumes, rate limits, SLAs and enterprise security.

Who it suits

Tavily suits developers building chatbots, research agents and retrieval-augmented generation apps that need current web information, and teams that would rather not run their own scraping and search infrastructure.

Things to consider

Check how credits are counted for advanced search depth, extraction and crawling, as heavier operations may cost more. Respect site terms when extracting content at scale. Web results can still be wrong or biased, so design your app to cite sources and let users verify them. Monitor usage closely once an agent runs automatically.

A typical integration takes a few lines of code using the official Python or JavaScript SDKs, and Tavily can also be connected to popular agent frameworks.