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 grainulation · MCP Server · ★ 86
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is grainulator safe to install? View the security audit →
Grainulator Research that compiles. Ask a question. Get a multi-pass investigation with typed claims, tension detection, and a confidence-graded answer. Not a chatbot — a research sprint that runs in under 60 seconds. What it does Multi-pass investigation — 3 research passes build evidence from different angles before synthesizing an answer Typed claims, not vibes — every finding is tagged as factual, constraint, risk, recommendation, or estimate with an ev
| Stars | 86 |
| Forks | 7 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.2297040663987/100 |
| Last Updated | 2026-09-22 |
| Created | 2026-03-21 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~15k |
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grainulator is Research that compiles.. It is categorized as a MCP Server with 86 GitHub stars.
grainulator is primarily written in JavaScript. It covers topics such as agent-framework, ai-agent, claude.
You can find installation instructions and usage details in the grainulator GitHub repository at github.com/grainulation/grainulator. The project has 86 stars and 7 forks, indicating an active community.
grainulator is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to grainulator on Agent Skills Hub include xclaude-plugin, claude-emporium, DashClaw. 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: