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 archestra-ai · MCP Server · ★ 4.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is archestra safe to install? View the security audit →
MCP-native Secure AI Platform Simplify AI usage in your company, providing user-friendly MCP toolbox, observability and control built on a strong security foundation. Getting Started Releases Slack Community For Platform teams: Mitigate MCP chaos, move MCP servers from individual machines to a centralized orchestrator Manage how MCP access data and credentials usage Mitigate data exfiltration risks Manage AI costs AI Observability For Developers: Deploy your MCP servers org-wide Build and deploy agents without worrying about security For Management: Bring 1-click MCP adoption to the whole organization for technical and non-technical users Reduce AI costs up to 96% Get full visibility on AI adoption, usage
| Stars | 4,298 |
| Forks | 1,211 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 55.4100242508898/100 |
| Open Issues | 39 |
| Last Updated | 2026-09-23 |
| Created | 2025-07-15 |
| Platforms | claude-code, cli, gemini, mcp, node |
| Est. Tokens | ~15k |
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程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Pr
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archestra is Enterprise AI Platform with guardrails, MCP registry, gateway & orchestrator. It is categorized as a MCP Server with 4.3k GitHub stars.
archestra is primarily written in TypeScript. It covers topics such as a2a, a2a-mcp, acp.
You can find installation instructions and usage details in the archestra GitHub repository at github.com/archestra-ai/archestra. The project has 4.3k stars and 1211 forks, indicating an active community.
The top alternatives to archestra on Agent Skills Hub include mcp-use, deepchat, better-chatbot. 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: