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 lakevision-project · MCP Server · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lakevision safe to install? View the security audit →
Lakevision Lakevision is a tool that provides insights into your Data Lakehouse based on the Apache Iceberg table format. It lists every nam
| Stars | 52 |
| Forks | 14 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66.7726960871211/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-01 |
| Created | 2024-07-30 |
| Platforms | aws, mcp, python |
| Est. Tokens | ~16k |
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lakevision is Lakevision is a tool which provides insights into your Apache Iceberg based Data Lakehouse.. It is categorized as a MCP Server with 52 GitHub stars.
lakevision is primarily written in Python. It covers topics such as apache, aws-s3, carbon-components-svelte.
You can find installation instructions and usage details in the lakevision GitHub repository at github.com/lakevision-project/lakevision. The project has 52 stars and 14 forks, indicating an active community.
lakevision is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to lakevision on Agent Skills Hub include openquok-monorepo, shadcn-svelte-mcp, facebook-ads-library-mcp. 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: