by metedata · MCP Server · ★ 66
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Your feedback layer for AI collaboration. Point at anything on your Mac - text, screenshots, web elements, or voice - and your agent reads and resolves your comments over MCP.
| Stars | 66 |
| Forks | 4 |
| Language | Swift |
| Category | MCP Server |
| License | MIT |
| Quality Score | 55.6598359308749/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-09 |
| Created | 2026-08-10 |
| Platforms | browser, mcp |
| Est. Tokens | ~15k |
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Remarc is Your feedback layer for AI collaboration. Point at anything on your Mac - text, screenshots, web elements, or voice - and your agent reads and resolves your comments over MCP.. It is categorized as a MCP Server with 66 GitHub stars.
Remarc is primarily written in Swift. It covers topics such as ai-agents, developer-tools, macos.
You can find installation instructions and usage details in the Remarc GitHub repository at github.com/metedata/Remarc. The project has 66 stars and 4 forks, indicating an active community.
Remarc is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Remarc on Agent Skills Hub include ContextKit, toolhive-studio, claude-emporium. 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: