knowledge-rag — security grade SAFE, quality 71/100

Security audit verdict: SAFE · quality 71/100

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 lyonzin · MCP Server · ★ 280

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is knowledge-rag safe to install? View the security audit →

About knowledge-rag

Knowledge RAG LLMs don't know your docs. Every conversation starts from zero. Your notes, writeups, internal procedures, PDFs — none of it exists to your AI assistant. Cloud RAG solutions leak your private data. Local ones require Docker, Ollama, and 15 minutes of setup before a single query. Knowledge RAG fixes this. One , zero external servers. Your documents become instantly searchable inside Claude Code — with reranking precision that actually finds what you need. 12 MCP Tools | Hybrid Search + Cross-Encoder Reranking

antigravityclaudeclaude-codeclaude-code-clicodexcursor-aidocument-searchhybrid-searchinteligencia-artificialknowledge-base

Quick Facts

Stars280
Forks40
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70.9040071043056/100
Open Issues6
Last Updated2026-09-22
Created2026-02-05
Platformsclaude-code, cli, codex, mcp, python
Est. Tokens~25k

knowledge-rag alternative? Top 6 similar tools

Looking for a knowledge-rag alternative? If you're comparing knowledge-rag with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • Agent-Fusion by krokozyab · ⭐ 72

    Agent Fusion is a local RAG semantic search engine that gives AI agents instant access to your code, documenta

  • claude-mem-lite by sdsrss · ⭐ 61

    Persistent long-term memory for Claude Code via MCP — captures coding decisions, bugfixes, and context across

  • deepcontext-mcp by Wildcard-Official · ⭐ 278

    DeepContext is an MCP server that adds symbol-aware semantic search to Claude Code, Codex CLI, and other agent

  • Axon.MCP.Server by ali-kamali · ⭐ 167

    Transform your codebase into an intelligent knowledge base for AI-powered development with Cursor IDE, Google

  • seline by tercumantanumut · ⭐ 143

    Seline is a local-first AI desktop application that brings together conversational AI, visual generation tools

  • pdf-mcp by jztan · ⭐ 136

    MCP server that lets Claude Code and other AI agents read and search large PDFs, one file or a whole folder: a

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Frequently Asked Questions

What is knowledge-rag?

knowledge-rag is Local RAG MCP server for Claude Code — hybrid search (semantic + BM25), cross-encoder reranking, 13 MCP tools, 20 format parsers. Zero external servers, zero API keys.. It is categorized as a MCP Server with 280 GitHub stars.

What programming language is knowledge-rag written in?

knowledge-rag is primarily written in Python. It covers topics such as antigravity, claude, claude-code.

How do I install or use knowledge-rag?

You can find installation instructions and usage details in the knowledge-rag GitHub repository at github.com/lyonzin/knowledge-rag. The project has 280 stars and 40 forks, indicating an active community.

What license does knowledge-rag use?

knowledge-rag is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to knowledge-rag?

The top alternatives to knowledge-rag on Agent Skills Hub include Agent-Fusion, claude-mem-lite, deepcontext-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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