How to Use Tavily

A beginner-friendly guide to getting started with Tavily in 2026.

Price Free plan available
Best For ai developers, llm builders, rag applications
Rating ★★★★ 4.3/5

Getting Started: Step by Step

1

Create your Tavily account

Visit Tavily's website and sign up for a free account. You'll need an email address to get started.

2

Set up your workspace

Once signed in, configure your Tavily workspace. Set your preferences, invite team members if needed, and customize the interface to match your workflow.

3

Explore search-api

One of Tavily's key features is search-api. Navigate to this feature and experiment with it to understand how it fits into your workflow.

4

Explore content-extraction

One of Tavily's key features is content-extraction. Navigate to this feature and experiment with it to understand how it fits into your workflow.

5

Explore topic-search

One of Tavily's key features is topic-search. Navigate to this feature and experiment with it to understand how it fits into your workflow.

6

Integrate with your existing tools

Connect Tavily with the other tools you use daily. Most integrations can be set up in the settings or integrations panel.

7

Start using it for real work

Now that you're set up, start using Tavily for actual tasks. The best way to learn is by doing — don't worry about getting everything perfect right away.

Pro Tips

  • Start with the free plan or trial to explore Tavily's capabilities before committing to a paid subscription.
  • Use keyboard shortcuts to speed up your workflow — most tools have extensive shortcut systems.
  • Check Tavily's official documentation and community forums for advanced tips and best practices.
  • Review your workflow after 2 weeks of use and adjust your setup based on what's working and what isn't.

Key Features to Explore

search-api
content-extraction
topic-search
news-search
filtering
ai-optimized-results

Alternatives to Consider

If Tavily isn't the right fit, here are some similar tools:

Ready to Try Tavily?

Search API built specifically for AI agents and LLM applications, providing optimized search results with content extraction for retrieval-augmented generation.

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