AgentSkillsCN

tavily

Tavily AI搜索API:专为大语言模型应用而生,支持网页搜索、内容提取、站点爬取、地图绘制与研究探索。关键词:Tavily、AI搜索、RAG、网页搜索API、LLM大语言模型搜索、内容提取、站点爬取、地图绘制、研究探索、tavily-python。

SKILL.md
--- frontmatter
name: tavily
description: "Tavily AI search API for LLM applications: web search, content extraction, site crawling, mapping, and research. Keywords: Tavily, AI search, RAG, web search API, LLM search, extract, crawl, map, research, tavily-python."
version: "0.7.21"
release_date: "2026-01-30"

# Tavily

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

## 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

bash
# Python
pip install tavily-python

# JavaScript
npm i @tavily/core

Quick Start

Python

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

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

bash
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

APIPurposeCredits
SearchWeb search optimized for LLMs1-2 per request
ExtractExtract content from URLs1-2 per 5 URLs
MapMap website structure1-2 per 10 pages
CrawlCrawl + extract from sitesMap + Extract
ResearchAutonomous deep research (beta)4-250 per task

Pricing & Credits

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

PlanCredits/monthPrice/credit
Researcher1,000Free
Project4,000$0.0075
Bootstrap15,000$0.0067
Startup38,000$0.0058
Growth100,000$0.005
Pay-as-goPer usage$0.008

Credit Costs

APIBasicAdvanced
Search12
Extract1/5 URLs2/5 URLs
Map1/10 pages2/10 pages
CrawlMap + Extract costs
Research (mini)4-110-
Research (pro)15-250-

Rate Limits

EnvironmentRPM (requests/min)
Development100
Production1,000

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.

python
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

python
{
    "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.

python
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.

python
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.

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

Research API (Beta)

Autonomous deep research on complex topics.

python
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?

FeatureTraditional SearchTavily
OutputURLs + snippetsFull content
ScrapingManualBuilt-in
LLM optimizationNonePurpose-built
FilteringManualAI-powered
Context limitsNot handledOptimized

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

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

Links