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 shredEngineer · MCP Server · ★ 64
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Archive-Agent safe to install? View the security audit →
Archive Agent An intelligent file indexer with powerful AI search (RAG engine), automatic OCR, and a seamless MCP interface. Archive Agent brings RAG to your command line and connects to your tools via MCP — it's not a chatbot. Find what you need with natural language Unlock your documents with semantic AI search & query Files are split using semantic chunking with context headers and committed to a local database. RAG engine¹ uses reranking and expanding of retrieved chunks ¹ [Retrieval Augm
| Stars | 64 |
| Forks | 9 |
| Language | Python |
| Category | MCP Server |
| License | GPL-3.0 |
| Quality Score | 65.4078819470021/100 |
| Open Issues | 17 |
| Last Updated | 2026-09-24 |
| Created | 2025-03-30 |
| Platforms | mcp, python |
| Est. Tokens | ~25k |
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Archive-Agent is Find your files with natural language and ask questions.. It is categorized as a MCP Server with 64 GitHub stars.
Archive-Agent is primarily written in Python. It covers topics such as lm-studio, mcp, mcp-server.
You can find installation instructions and usage details in the Archive-Agent GitHub repository at github.com/shredEngineer/Archive-Agent. The project has 64 stars and 9 forks, indicating an active community.
Archive-Agent is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to Archive-Agent on Agent Skills Hub include PolyMCP, pdf-mcp, pdfmux. 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: