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 mastra-ai · MCP Server · ★ 28.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mastra safe to install? View the security audit →
Mastra Mastra is a framework for building AI-powered applications and agents with a modern TypeScript stack. It includes everything you need to go from early prototypes to production-ready applications. Mastra integrates with frontend and backend frameworks like React, Next.js, and Node, or you can deploy it anywhere as a standalone server. It's the easiest way to build, tune, and scale reliable AI products. Why Mastra? Purpose-built for TypeScript and designed around established AI patterns, Mastra gives you everything you need to build great AI applications out-of-the-box.
| Stars | 28,268 |
| Forks | 2,843 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 60.5943976285191/100 |
| Open Issues | 454 |
| Last Updated | 2026-09-23 |
| Created | 2024-08-06 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
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mastra is Mastra is the modern TypeScript framework for AI-powered applications and agents.. It is categorized as a MCP Server with 28.3k GitHub stars.
mastra is primarily written in TypeScript. It covers topics such as agents, ai, chatbots.
You can find installation instructions and usage details in the mastra GitHub repository at github.com/mastra-ai/mastra. The project has 28.3k stars and 2843 forks, indicating an active community.
The top alternatives to mastra on Agent Skills Hub include voltagent, CopilotKit, composio. 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: