llm-wiki MCP Server
Pratiyush/llm-wiki
[](https://agentrank-ai.com/tool/Pratiyush--llm-wiki/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) LLM-powered knowledge base from your Claude Code, Codex CLI, Copilot, Cursor & Gemini sessions. Karpathy's LLM Wiki pattern — implemented and shipped.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
Pratiyush/llm-wiki is a Python tool licensed under MIT. LLM-powered knowledge base from your Claude Code, Codex CLI, Copilot, Cursor & Gemini sessions. Karpathy's LLM Wiki pattern — implemented and shipped. Topics: ai, claude-code, codex-cli, cursor, developer-tools, karpathy, knowledge-base, llm, llm-wiki, markdown, mcp, open-source, python, static-site, wiki, cli, copilot, gemini-cli, obsidian, session-history.
Ranked #4165 out of 24846 indexed tools.
Ecosystem
Score Breakdown
397 stars → growing community
Last commit 4mo ago → stale
444/473 issues closed → responsive maintainer
5 contributors → small team
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
Matched Queries
From the README
# llmwiki > **LLM-powered knowledge base from your Claude Code, Codex CLI, Cursor, Gemini CLI, and Obsidian sessions.** > Built on [Andrej Karpathy's LLM Wiki pattern](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f). ## 👉 Live demo: **[pratiyush.github.io/llm-wiki](https://pratiyush.github.io/llm-wiki/)** Rebuilt on every `master` push from the synthetic sessions in [`examples/demo-sessions/`](examples/demo-sessions). No personal data. Shows every feature of the real tool (activity heatmap, tool charts, token usage, model info cards, vs-comparisons, project topics) running against safe reference data. --- Every Claude Code, Codex CLI, Copilot, Cursor, and Gemini CLI session writes a full transcript to disk. You already have hundreds of them and never look at them again. **llmwiki** turns that dormant history into a beautiful, searchable, interlinked knowledge base — locally, in two commands. Plus, it produces AI-consumable exports (`llms.txt`, `llms-full.txt`,Read full README on GitHub →
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