# Browser Use

> Use this tool when you need to automate web interactions without complex coding, such as executing browser tasks using plain language instructions. It solves problems like automating data entry, web scraping, and testing, by providing a simple API for browser automation. The tool takes natural language commands as input and outputs automated browser actions, making it ideal for use cases requiring efficient and intuitive web automation.

Canonical page: https://skillsregistry.net/skills/jonnyhoff-browser-use  
JSON: https://api.skillsregistry.net/v1/skills/jonnyhoff-browser-use

## Description

This MCP server implementation provides browser automation capabilities through a simple API. It utilizes FastMCP for creating the API server, browser-use for browser automation, and OpenAI's GPT models to interpret natural language commands. The server enables executing browser tasks using plain language instructions, making it useful for scenarios requiring automated web interactions without complex coding.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** browser-automation
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/jonnyhoff-browser-use)
- **Repository:** <https://github.com/jonnyhoff/mcp-browser-use>

## 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": "jonnyhoff-browser-use"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jonnyhoff-browser-use` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jonnyhoff-browser-use/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