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llm-wiki-kit
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llm-wiki-kit

Active·★ 55·MIT·Updated 2026-04-08
★ Trending★ RAG / Knowledge Base★ Memory & Context

Stop re-explaining your research to your AI agent. Persistent, LLM-maintained wikis that compound over time. Drop PDFs, URLs, YouTube — your agent remembers forever. Based on Karpathy's LLM Wiki pattern.

llm-wiki-kit gives your AI agent a persistent, structured memory that compounds over time. Drop PDFs, URLs, YouTube videos — your agent builds a wiki, connects the dots, and remembers everything across sessions. It works with Claude, Codex, Cursor, Windsurf, and any MCP-compatible agent.

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Code AssistantWorkflow AutomationRAG / Knowledge BaseMulti-AgentBrowser AutomationLLM InfraDev ToolingObservability

Not affiliated with Anthropic, OpenAI or Microsoft.

#ai-agent#knowledge-base#llm#llm-tools#mcp#mcp-server#mcp-servers
$ Install
$ pip install "llm-wiki-kit[all] @ git+https://github.com/iamsashank09/llm-wiki-kit.git"
↗ Visit site★ GitHub
01

Features

01Multi-format ingest (PDFs, URLs, YouTube, markdown)
02Auto cross-referencing with wiki links
03Persistent memory across sessions
04Full-text search via SQLite FTS5
05Health checks (broken links, orphan pages)
02

Compatibility

Claude
Claude Desktop
Verified via docs
Codex
OpenAI Codex
Verified via docs
Cursor
Cursor
Verified via docs
Windsurf
Windsurf
Verified via docs
03

Quick start

1
$ pip install "llm-wiki-kit[all] @ git+https://github.com/iamsashank09/llm-wiki-kit.git"
04

Use cases

↳Research: feed papers and ask synthesis questions across sources
↳Technical onboarding: ingest codebase docs for architecture queries
↳Learning: build a personalized wiki from tutorials and blog posts
05

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Related searches

llm-wiki-kit AlternativesBest Memory & Context Tools 2026Open Source Memory & Contextllm-wiki-kit Tutorialllm-wiki-kit Vs Competitorsai-agentknowledge-basellm

Comments

Log in to leave a comment
  • Oakley Lee
    Oakley LeeMay 23, 2026

    Setup was straightforward, lightweight config and running in minutes. Good documentation, reduces onboarding time.

  • S
    Shawn PatelApr 5, 2026

    Handles persistent operations that other servers miss — persistent, llm-maintained wikis that compound over time. The maintainers are responsive to issues.

  • B
    Blake LewisApr 2, 2026

    Research via MCP is exactly the right abstraction — stop re-explaining your research to your ai agent. Runs fine on Apple Silicon.

  • D
    Dylan ThompsonMar 30, 2026

    Integrates cleanly into well-designed workflows — stop re-explaining your research to your ai agent. Integrates well with existing stop setups.

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1mo ago
StatusActive
LicenseMIT
CategoryMemory & Context
Trend (30d)
+2.2↑ 0.5%
Links
Documentation↗Discussion↗Issues↗Releases↗

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