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 macOS26 · MCP Server · ★ 562
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Agent safe to install? View the security audit →
🦾 Agent! for macOS 26.4+ Agentic AI for your Mac Desktop Open Source replacement for Claude Code, Cursor, Cline, OpenClaw What's New 🚀 Apple AI as a real tool-calling agent: On-device Apple Intelligence (FoundationModels.Tool) handles UI automation r
| Stars | 562 |
| Forks | 58 |
| Language | Swift |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.3771534191917/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-05 |
| Created | 2026-03-11 |
| Platforms | claude-code, gemini, mcp |
| Est. Tokens | ~5143k |
Looking for a Agent alternative? If you're comparing Agent 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.
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Agent is Agent! Is a native macOS App that works with any LLM [local and cloud], [open source and paid] Claude, OpenAI, Gemini, Ollama, Qwen, Hugging Face, and 12 more. Writes code, builds Xcode projects, bump. It is categorized as a MCP Server with 562 GitHub stars.
Agent is primarily written in Swift. It covers topics such as accessibility, agentic-framework, agentic-workflow.
You can find installation instructions and usage details in the Agent GitHub repository at github.com/macOS26/Agent. The project has 562 stars and 58 forks, indicating an active community.
Agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Agent on Agent Skills Hub include apple-mail-mcp, xclaude-plugin, py-gpt. 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: