by Oshayr · MCP Server · ★ 51
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
claude plugin install ./llm-wikiTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 51 |
| Forks | 1 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68/100 |
| Open Issues | 2 |
| Last Updated | 2026-04-26 |
| Created | 2026-04-09 |
| Platforms | browser, claude-code, mcp, python |
| Est. Tokens | ~17k |
llm-wiki An autonomous knowledge base that grows as you work. LLM Wiki is a Claude Code plugin that captures research, ideas, and decisions into an interlinked wiki with semantic search, automatic research, and a Wikipedia-style web UI. Knowledge compounds over time — the more you use it, the smarter it gets.
Looking for a LLM-Wiki alternative? If you're comparing LLM-Wiki 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.
Karpathy's LLM Wiki idea as a product — an AI that builds and maintains a markdown wiki from your notes and so
Andrej Karpathy's LLM Wiki pattern as a skill & Claude Code plugin — turn accumulated sources into a self-main
A compounding LLM-wiki, best fit as a personal second brain that organizes and updates itself as it grows, zer
Karpathy's LLM Wiki idea as a product — an AI that builds and maintains a markdown wiki from your notes and so
Memoriki - LLM Wiki + MemPalace. Personal knowledge base with real memory.
Second Brain automation for Obsidian vaults — entity management, ingestion, compression, and sync via Claude C
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: