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 etsd-tech · MCP Server · ★ 591
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-pointer safe to install? View the security audit →
👆 MCP Pointer Point to browser DOM elements for agentic coding tools via MCP! MCP Pointer is a local tool combining an MCP Server with a Chrome Extension: 🖥️ MCP Server (Node.js package) - Bridges between the browser and AI tools via the Model Context Protocol 🌐 Chrome Extension - Captures DOM element selections in the browser using The extension lets you visually select DOM elements in the browser, and the MCP server makes this textual context available to
| Stars | 591 |
| Forks | 58 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.6952139593045/100 |
| Open Issues | 7 |
| Last Updated | 2025-11-12 |
| Created | 2025-09-01 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~32k |
These tools work well together with mcp-pointer for enhanced workflows:
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mcp-pointer is MCP tool: let you point at DOM elements for your favorite agentic coding tool. Let AI see what you see.. It is categorized as a MCP Server with 591 GitHub stars.
mcp-pointer is primarily written in TypeScript. It covers topics such as agentic-coding, browser, claude-code.
You can find installation instructions and usage details in the mcp-pointer GitHub repository at github.com/etsd-tech/mcp-pointer. The project has 591 stars and 58 forks, indicating an active community.
mcp-pointer is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-pointer on Agent Skills Hub include vibetest-use, browser-use-mcp-server, Claude-Skills. 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: