tavily

name	tavily
description	Tavily AI search API for LLM applications: web search, content extraction, site crawling, mapping, and research. Use when integrating real-time web search into LLM apps, extracting content from URLs, crawling sites, or building RAG pipelines with web data. Keywords: Tavily, AI search, RAG, web search API, LLM search, extract, crawl, map, research, tavily-python.
metadata	{"version":"0.7.27","release_date":"2026-07-30"}

Tavily

AI-optimized search engine for building LLM applications with real-time web data.

Links

• Documentation
• Releases
• GitHub
• PyPI

Quick Navigation

Topic	Reference
REST API	api.md
Python SDK	python.md
JavaScript SDK	javascript.md
Best Practices	best-practices.md
Integrations	integrations.md

When to Use

• Building RAG applications with real-time web data
• AI agents that need current information
• Content extraction from web pages
• Site crawling with AI-guided instructions
• Autonomous research tasks

Installation

Install: pip install tavily-python (Python) or npm i @tavily/core (JavaScript).

Quick Start

Python

from tavily import TavilyClient

client = TavilyClient(api_key="tvly-YOUR_API_KEY")
response = client.search("What is the latest news about AI?")
print(response)

JavaScript

import { tavily } from "@tavily/core";

const client = tavily({ apiKey: "tvly-YOUR_API_KEY" });
const response = await client.search("What is the latest news about AI?");
console.log(response);

cURL

curl -X POST https://api.tavily.com/search \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer tvly-YOUR_API_KEY" \
  -d '{"query": "What is the latest news about AI?"}'

Core APIs

API	Purpose	Credits
Search	Web search optimized for LLMs	1-2 per request
Extract	Extract content from URLs	1-2 per 5 URLs
Map	Map website structure	1-2 per 10 pages
Crawl	Crawl + extract from sites	Map + Extract
Research	Autonomous deep research (beta)	4-250 per task

Pricing & Credits

Free tier: 1,000 credits/month (no credit card required)

Plan	Credits/month	Price/credit
Researcher	1,000	Free
Project	4,000	$0.0075
Bootstrap	15,000	$0.0067
Startup	38,000	$0.0058
Growth	100,000	$0.005
Pay-as-go	Per usage	$0.008

Credit Costs

API	Basic	Advanced
Search	1	2
Extract	1/5 URLs	2/5 URLs
Map	1/10 pages	2/10 pages
Crawl	Map + Extract costs
Research (mini)	4-110	-
Research (pro)	15-250	-

Rate Limits

Environment	RPM (requests/min)
Development	100
Production	1,000

Note: Crawl endpoint limited to 100 RPM for both environments.

Production keys require paid plan or PAYGO enabled.

Search API

Primary endpoint for LLM-optimized web search.

response = client.search(
    query="Latest AI developments",
    search_depth="advanced",      # "basic" (1 credit) or "advanced" (2 credits)
    max_results=10,               # 1-20 results
    include_answer=True,          # Include AI-generated answer
    include_raw_content=False,    # Include raw HTML
    include_domains=["arxiv.org"],  # Filter to specific domains
    exclude_domains=["pinterest.com"]  # Exclude domains
)

Response Structure

{
    "query": "...",
    "answer": "AI-generated summary...",  # if include_answer=True
    "results": [
        {
            "title": "Page Title",
            "url": "https://...",
            "content": "Extracted relevant content...",
            "score": 0.95,
            "raw_content": "..."  # if include_raw_content=True
        }
    ]
}

Extract API

Extract content from specific URLs.

response = client.extract(
    urls=["https://example.com/article1", "https://example.com/article2"],
    extract_depth="basic"  # "basic" or "advanced"
)

Crawl API

Crawl websites with AI-guided instructions.

response = client.crawl(
    url="https://docs.example.com",
    instructions="Find all pages about Python SDK",  # Optional AI guidance
    max_depth=2,
    limit=50
)

Map API

Get website structure without extracting content.

response = client.map(
    url="https://docs.example.com",
    instructions="Find documentation pages"  # Optional
)

Research API (Beta)

Autonomous deep research on complex topics.

response = client.research(
    input="What are the implications of quantum computing on cryptography?",
    model="pro"  # "pro" (15-250 credits) or "mini" (4-110 credits)
)

Why Tavily?

Feature	Traditional Search	Tavily
Output	URLs + snippets	Full content
Scraping	Manual	Built-in
LLM optimization	None	Purpose-built
Filtering	Manual	AI-powered
Context limits	Not handled	Optimized

Best Practices

1. Use search_depth="basic" for simple queries (saves credits)
2. Use include_answer=True for quick summaries
3. Filter domains to improve relevance
4. Use Extract when you know specific URLs
5. Use Research for complex, multi-step queries
6. Use Python keyless mode only for trials; it supports search() and extract() only and remains rate-limited

Prohibitions

• Do not expose API keys in client-side code

• Do not exceed rate limits (implement backoff)

• Do not scrape sites that block Tavily crawler

• API Playground

• Documentation

• Community