---
id: itechmeat/llm-code/tavily
version: "18725b5e"
license: MIT
install: manual
updated: 2026-07-18
---

# tavily — Tavily is an AI-optimized search engine built for language model applications that need current web data. It provides web search, URL content extraction, site crawling, and autonomous research capabilities—all designed to return results formatted for LLM consumption rather than human browsing.

Publisher: itechmeat · Stars: 21 · Updated: 2026-07-18

Install (manual): `git clone https://github.com/itechmeat/llm-code`

## SKILL.md

# Tavily

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

## Links

- [Documentation](https://docs.tavily.com/)
- [Releases](https://pypi.org/project/tavily-python/#history)
- [GitHub](https://github.com/tavily-ai/tavily-python)
- [PyPI](https://pypi.org/project/tavily-python/)

## Quick Navigation

| Topic          | Reference                                         |
| -------------- | ------------------------------------------------- |
| REST API       | [api.md](references/api.md)                       |
| Python SDK     | [python.md](references/python.md)                 |
| JavaScript SDK | [javascript.md](references/javascript.md)         |
| Best Practices | [best-practices.md](references/best-practices.md) |
| Integrations   | [integrations.md](references/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

```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

| 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.

```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?

| 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](https://app.tavily.com/playground)
- [Documentation](https://docs.tavily.com)
- [Community](https://discord.gg/tavily)


[View on SkillFed](https://skillfed.io/itechmeat/llm-code/tavily) · [View on GitHub](https://github.com/itechmeat/llm-code)