No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by mozilla · MCP Server · ★ 432
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is firefox-devtools-mcp safe to install? View the security audit →
Firefox DevTools MCP Model Context Protocol server for automating Firefox via WebDriver BiDi (through Selenium WebDriver). Works with Claude Code, Claude Desktop, Cursor, Cline and other MCP clients. Repository: https://github.com/mozilla/firefox-devtools-mcp Note: This MCP server requires a local Firefox browser installation and cannot run on cloud hosting services like glama.ai. Use to run locally, or use Docker with the provided Dockerfile. Requirements Node.js ≥ 20.19.0 Firefox 100+ installed (auto‑detected, or pass ) Install and use with Claude Code (npx) Recommended: use npx so you always run the latest published version from npm. Option A — Claude Code CLI bash claude mcp add firefox-devtools npx fir
| Stars | 432 |
| Forks | 64 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 74.1205349603925/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-22 |
| Created | 2025-10-08 |
| Platforms | browser, claude-code, docker, mcp, node |
| Est. Tokens | ~16k |
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firefox-devtools-mcp is Model Context Protocol server for Firefox DevTools - enables AI assistants to inspect and control Firefox browser through WebDriver BiDi. It is categorized as a MCP Server with 432 GitHub stars.
firefox-devtools-mcp is primarily written in TypeScript. It covers topics such as claude-code, firefox, mcp.
You can find installation instructions and usage details in the firefox-devtools-mcp GitHub repository at github.com/mozilla/firefox-devtools-mcp. The project has 432 stars and 64 forks, indicating an active community.
The top alternatives to firefox-devtools-mcp on Agent Skills Hub include MeiGen-AI-Design-MCP, mysql_mcp_server, cclsp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: