> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Tavily extract integration
> Integrate with the Tavily extract tool using LangChain JavaScript.
[Tavily](https://tavily.com/) is a search engine built specifically for AI agents (LLMs), delivering real-time, accurate, and factual results at speed. Tavily offers an [Extract](https://docs.tavily.com/documentation/api-reference/endpoint/extract) endpoint that can be used to extract the cleaned, parsed content of one or more URLs.
## Overview
### Integration details
| Class | Package | [PY support](https://python.langchain.com/docs/integrations/tools/tavily_extract) | Downloads | Version |
| :------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------- | :-------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------: |
| [`TavilyExtract`](https://reference.langchain.com/javascript/langchain-tavily/TavilyExtract) | [`@langchain/tavily`](https://www.npmjs.com/package/@langchain/tavily) | ✅ |  |  |
### Tool features
| [Returns artifact](/oss/javascript/langchain/tools) | Native async | Return data | Pricing |
| :-------------------------------------------------: | :----------: | :--------------------: | :------------------------: |
| ❌ | ✅ | raw content and images | 1,000 free credits / month |
## Setup
The integration lives in the `@langchain/tavily` package, which you can install as shown below:
```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
npm install @langchain/tavily @langchain/core
```
```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
yarn add @langchain/tavily @langchain/core
```
```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pnpm add @langchain/tavily @langchain/core
```
### Credentials
[Set up a Tavily API key](https://app.tavily.com) and set it as an environment variable named `TAVILY_API_KEY`.
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
process.env.TAVILY_API_KEY = "YOUR_API_KEY"
```
It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com?utm_source=docs\&utm_medium=cta\&utm_campaign=langsmith-signup\&utm_content=oss-javascript-integrations-tools-tavily_extract) for best-in-class observability:
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
process.env.LANGSMITH_TRACING="true"
process.env.LANGSMITH_API_KEY="your-api-key"
```
## Instantiation
The tool accepts the following parameters during instantiation:
* `extractDepth` (optional, string): Depth of the extraction, either `"basic"` or `"advanced"`. Default is `"basic"`.
* `includeImages` (optional, boolean): Whether to include images in the extraction. Default is `false`.
* `format` (optional, string): Content format. `"markdown"` or `"text"`. Default is `"markdown"`.
* `includeFavicon` (optional, boolean): Include each result's favicon URL. Default is `false`.
For a comprehensive overview of the available parameters, refer to the [Tavily Extract API documentation](https://docs.tavily.com/documentation/api-reference/endpoint/extract).
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import { TavilyExtract } from "@langchain/tavily";
const tool = new TavilyExtract({
extractDepth: "basic",
includeImages: false,
});
```
## Invocation
### [Invoke directly with args](/oss/javascript/langchain/tools)
The Tavily extract tool accepts the following arguments during invocation:
* `urls` (required): A list of URLs to extract content from.
* The following arguments can also be set during invocation: `extractDepth`, `includeImages`.
NOTE: The optional arguments are available for agents to dynamically set. If you set an argument during instantiation and then invoke the tool with a different value, the tool will use the value you passed during invocation.
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
await tool.invoke({ urls: ["https://en.wikipedia.org/wiki/Lionel_Messi"] });
```
```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
{
results: [{
url: 'https://en.wikipedia.org/wiki/Lionel_Messi',
raw_content: 'Lionel Messi - Wikipedia\nJump to content\nMain menu\n... (truncated)',
images: []
}],
failed_results: [],
response_time: 0.02
}
```
### [Invoke with ToolCall](/oss/javascript/langchain/tools)
We can also invoke the tool with a model-generated `ToolCall`, in which case a [`ToolMessage`](https://reference.langchain.com/javascript/langchain-core/messages/ToolMessage) will be returned:
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
// This is usually generated by a model, but we'll create a tool call directly for demo purposes.
const modelGeneratedToolCall = {
args: { urls: ["https://en.wikipedia.org/wiki/Lionel_Messi"] },
id: "1",
name: tool.name,
type: "tool_call",
};
const toolMsg = await tool.invoke(modelGeneratedToolCall);
// The content is a JSON string of results
console.log(toolMsg.content.slice(0, 400));
```
```json theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
{"results": [{"url": "https://en.wikipedia.org/wiki/Lionel_Messi", "raw_content": "Lionel Messi - Wikipedia\nJump to content\nMain menu\nMain menu\nmove to sidebar hide\nNavigation\n\nMain page\nContents\nCurrent events\nRandom article\nAbout Wikipedia\nContact us\n\nContribute\n\nHelp\nLearn to edit\nCommunity portal\nRecent changes\nUpload file\nSpecial pages\n... (truncated)"}], "failed_results": [], "response_time": 0.02}
```
## Use within an agent
We can use the extract tool directly with a LangChain agent by passing it to `createAgent`. The agent can dynamically set the list of URLs and toggles like `extractDepth` and `includeImages` as part of its tool call.
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
// @lc-docs-hide-cell
import { ChatOpenAI } from "@langchain/openai";
const llm = new ChatOpenAI({
model: "gpt-5.5",
temperature: 0,
});
```
```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import { TavilyExtract } from "@langchain/tavily";
import { createAgent } from "langchain";
const tavilyExtractTool = new TavilyExtract();
const agent = createAgent({
model: llm,
tools: [tavilyExtractTool],
});
const userInput = "Summarize https://en.wikipedia.org/wiki/Albert_Einstein and https://en.wikipedia.org/wiki/Theoretical_physics.";
const stream = await agent.streamEvents(
{ messages: [["human", userInput]] },
{ version: "v3" },
);
for await (const snapshot of stream.values) {
const lastMsg = snapshot.messages[snapshot.messages.length - 1];
if (lastMsg.tool_calls?.length) {
console.dir(lastMsg.tool_calls, { depth: null });
} else if (lastMsg.content) {
console.log(lastMsg.content);
}
}
```
***
## API reference
For detailed documentation of all Tavily Extract API features and configurations head to the API reference: [docs.tavily.com/documentation/api-reference/endpoint/extract](https://docs.tavily.com/documentation/api-reference/endpoint/extract)
***
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