# Tavily — Search API Built for AI Agents & RAG

> Search API designed specifically for AI agents and RAG pipelines. Returns clean, LLM-ready results with content extraction, no HTML parsing needed. Official MCP server available. 5,000+ stars.

## Install

Merge the JSON below into your `.mcp.json`:

## Quick Use

Add to your `.mcp.json`:

```json
{
  "mcpServers": {
    "tavily": {
      "command": "npx",
      "args": ["-y", "tavily-mcp"],
      "env": {
        "TAVILY_API_KEY": "tvly-your-key"
      }
    }
  }
}
```

Get your free API key at [tavily.com](https://tavily.com). Restart Claude Code and ask: "Search the web for the latest MCP server releases."

---

## Intro

Tavily is a search API built specifically for AI agents and RAG pipelines with 5,000+ GitHub stars. Unlike Google or Bing APIs that return HTML snippets, Tavily returns clean, LLM-ready text with source attribution — no scraping or parsing needed. It includes an official MCP server, Python/JS SDKs, and integrations with LangChain, LlamaIndex, and CrewAI. Best for developers building AI agents that need real-time web knowledge. Works with: Claude Code, Cursor, LangChain, CrewAI, any MCP client. Setup time: under 1 minute.

---

## Why Tavily Over Google API

| Feature | Google Search API | Tavily |
|---------|------------------|--------|
| Output | HTML snippets | Clean text, LLM-ready |
| Content extraction | Manual scraping needed | Built-in |
| Source quality | All results | Filtered for relevance |
| Token efficiency | Wasteful (HTML tags) | Optimized for LLMs |
| Pricing | Per query | 1,000 free/month |

### MCP Tools Available

#### `tavily_search`
```
"Search for best practices for deploying Claude Code in enterprise"
```
Returns: clean text results with URLs and relevance scores.

#### `tavily_extract`
```
"Extract the main content from https://docs.anthropic.com/en/docs/agents"
```
Returns: clean markdown from any URL.

### Python SDK

```python
from tavily import TavilyClient

client = TavilyClient(api_key="tvly-...")

# Basic search
results = client.search("latest AI agent frameworks 2026")

# Advanced search with content extraction
results = client.search(
    query="Claude Code best practices",
    search_depth="advanced",
    include_raw_content=True,
    max_results=5
)

for r in results["results"]:
    print(f"{r['title']}: {r['content'][:200]}")
```

### Integration with Agent Frameworks

```python
# LangChain
from langchain_community.tools import TavilySearchResults
tool = TavilySearchResults(max_results=5)

# CrewAI
from crewai_tools import TavilySearchTool
search = TavilySearchTool()
```

### Key Stats
- 5,000+ GitHub stars
- 1,000 free searches/month
- LLM-optimized output
- MCP server + Python/JS SDKs
- LangChain, CrewAI integrations

### FAQ

**Q: What is Tavily?**
A: Tavily is a search API built for AI agents that returns clean, LLM-ready text results instead of HTML, with built-in content extraction and source attribution.

**Q: Is Tavily free?**
A: Free tier includes 1,000 searches/month. Paid plans for higher volume.

**Q: How is Tavily different from Firecrawl?**
A: Tavily is a search engine — it finds relevant pages. Firecrawl is a scraper — it extracts content from URLs you specify. They complement each other.

---

## Source & Thanks

> Created by [Tavily](https://github.com/tavily-ai). Licensed under MIT.
>
> [tavily](https://github.com/tavily-ai/tavily-python) — ⭐ 5,000+

Thanks for building the search engine AI agents actually need.

---

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## 快速使用

将以下配置添加到 `.mcp.json`:

```json
{
  "mcpServers": {
    "tavily": {
      "command": "npx",
      "args": ["-y", "tavily-mcp"],
      "env": { "TAVILY_API_KEY": "tvly-你的密钥" }
    }
  }
}
```

---

## 简介

Tavily 是一个专为 AI Agent 和 RAG 管道设计的搜索 API，GitHub 5,000+ stars。返回干净的 LLM 可用文本，无需 HTML 解析。提供 MCP 服务器、Python/JS SDK。适合构建需要实时网络知识的 AI Agent。

---

## 来源与感谢

> Created by [Tavily](https://github.com/tavily-ai). Licensed under MIT.
>
> [tavily](https://github.com/tavily-ai/tavily-python) — ⭐ 5,000+

---
Source: https://tokrepo.com/en/workflows/f73611a0-142f-4364-97dc-b57eb03473ad
Author: MCP Hub