# mcp-chrome

> mcp-chrome — femto-mcp-chrome. Use this tool when you need to automate Chrome browser interactions using AI, solving problems such as automated testing, data extraction, and workflow automation. It takes MCP protocol inputs and outputs controlled browser actions, allowing for seamless integration with AI agents. Ideal for use cases requiring programmatic browser control, such as web scraping, automated form filling, and browser-based automation tasks.

Canonical page: https://skillsregistry.net/skills/femto-mcp-chrome  
JSON: https://api.skillsregistry.net/v1/skills/femto-mcp-chrome

## Description

Control Chrome browser with AI using MCP protocol.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** browser-automation
- **Updated:** 2026-09-25

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/femto-mcp-chrome)

## 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": "femto-mcp-chrome"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/femto-mcp-chrome` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/femto-mcp-chrome/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