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by Laurent00TT · MCP Server · ★ 243
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is PharosRAG safe to install? View the security audit →
Pharos Turn PDFs, scans, docx, pptx and xlsx into a local knowledge base you can ask questions of — with enterprise access control and citations you can trace back to the page. Each RAG component was sharpened on its own, then folded into one repository: multi-identity auth, observability and systemd supervision come with it. A note on language. The code, CLI and commit history are in English; the documentation — including the 12-part learning series — is written in Chinese. This README is the English entry point and covers what the system is, how it is put together and how to run it. For anything deeper, you will be reading Chinese (or machine-translating it). The
| Stars | 243 |
| Forks | 0 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 51.8460768631138/100 |
| Last Updated | 2026-08-19 |
| Created | 2026-05-25 |
| Platforms | mcp, python |
| Est. Tokens | ~13k |
These tools work well together with PharosRAG for enhanced workflows:
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PharosRAG is Pharos — local-first agentic RAG for your team's document library: multi-format ingest, hybrid retrieval, enterprise ACL, dual HTTP + MCP exits.. It is categorized as a MCP Server with 243 GitHub stars.
PharosRAG is primarily written in Python. It covers topics such as agentic-rag, embeddings, fastapi.
You can find installation instructions and usage details in the PharosRAG GitHub repository at github.com/Laurent00TT/PharosRAG. The project has 243 stars and 0 forks, indicating an active community.
PharosRAG is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to PharosRAG on Agent Skills Hub include pdf-mcp, gno, CoWork-OS. 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: