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 tobocop2 · MCP Server · ★ 53
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lilbee safe to install? View the security audit →
Run and manage local AI models, and search everything you own with them, all in one program. Project site · Tutorial reels · PyPI · Obsidian plugin · REST API <img src="https://img.shields.io/badge/coverage-100%25-br
| Stars | 53 |
| Forks | 4 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 59.0238756282508/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-12 |
| Created | 2026-03-05 |
| Platforms | browser, cli, mcp, python |
| Est. Tokens | ~23k |
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lilbee is The whole local AI stack in one executable: it runs and manages local AI models across every GPU, and it's a search engine you can talk to, with cited answers from your files, code, and the web. MCP s. It is categorized as a MCP Server with 53 GitHub stars.
lilbee is primarily written in Python. It covers topics such as ai-search-engine, chat-with-documents, gguf.
You can find installation instructions and usage details in the lilbee GitHub repository at github.com/tobocop2/lilbee. The project has 53 stars and 4 forks, indicating an active community.
lilbee is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to lilbee on Agent Skills Hub include roampal, Deskdrop, open-jet. 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: