# Tavily Extract

> Use this tool when you need to extract web page content with ease, solving web scraping challenges and providing valuable data for projects. It takes a URL as input and returns the extracted content as output, utilizing the Tavily API for efficient data retrieval. Ideal for projects requiring web scraping capabilities, this tool simplifies the process with a simple interface and minimal setup.

Canonical page: https://skillsregistry.net/skills/algonacci-tavily-extract  
JSON: https://api.skillsregistry.net/v1/skills/algonacci-tavily-extract

## Description

This MCP server implementation provides a simple interface for extracting web page content using the Tavily API. It utilizes the FastMCP framework and exposes a single tool, 'extract_url', which takes a URL as input and returns the extracted content. The server requires a Tavily API key to be set as an environment variable and is designed for easy integration into projects that need web scraping capabilities.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/algonacci-tavily-extract)
- **Repository:** <https://github.com/algonacci/mcp-tavily-extract>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "algonacci-tavily-extract"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/algonacci-tavily-extract` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/algonacci-tavily-extract/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt