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 dralkh · MCP Server · ★ 74
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is seerai safe to install? View the security audit →
seerai seerai is an intelligent research assistant plugin for Zotero 9 that integrates AI-powered chat, advanced search, and data extraction capabilit
| Stars | 74 |
| Forks | 5 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.9426182101109/100 |
| Open Issues | 4 |
| Last Updated | 2026-07-09 |
| Created | 2025-12-10 |
| Platforms | mcp, node |
| Est. Tokens | ~18k |
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seerai is Zotero AI plugin Research assistant for Zotero 9. Chat with your library, run federated scholarly search, RAG, OCR, systematic reviews, and manage cloud storage. Includes standalone MCP, Agentic capab. It is categorized as a MCP Server with 74 GitHub stars.
seerai is primarily written in TypeScript. It covers topics such as academic-research, agent, ai.
You can find installation instructions and usage details in the seerai GitHub repository at github.com/dralkh/seerai. The project has 74 stars and 5 forks, indicating an active community.
seerai is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to seerai on Agent Skills Hub include ZotSeek, cli-anything-zotero, web-researcher-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: