by metedata · MCP Server · ★ 74
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/metedata/Remarc.gitTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 74 |
| Forks | 5 |
| Language | Swift |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64/100 |
| Open Issues | 1 |
| Last Updated | 2026-10-04 |
| Created | 2026-08-10 |
| Platforms | browser, mcp |
| Est. Tokens | ~16k |
Remarc Remarc is the feedback layer between you and your coding agent. Point at anything on your Mac: text, a screenshot, or a web element. Talk through a review or jot down a quick note. Remarc keeps the relevant context with each comment so your agent can take it from there.
These tools work well together with Remarc for enhanced workflows:
Looking for a Remarc alternative? If you're comparing Remarc with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Apple developer docs and WWDC transcripts with RAG retrieval and Jev relevance ranking.
Daymon puts your favorite AI to work 24/7. It schedules, remembers, and orchestrates your own virtual team. Fr
ToolHive is an application that allows you to install, manage and run MCP servers and connect them to AI agent
Claude Code context engineering & planning system for individual AI development workflows
🏛 [UNDER CONSTRUCTION] A (roman) claude plugin marketplace
A reimplementation of the Pokemon Red/Blue engine in Swift and SwiftUI
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: