LLM Wiki KitSAFE

Stop re-explaining your research to your AI agent every session.

[](https://opensource.org/licenses/MIT) [](https://www.python.org/downloads/)

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.

Based on Karpathy's LLM Wiki pattern. Works with Claude, Codex, Cursor, Windsurf, and any MCP-compatible agent.

https://github.com/user-attachments/assets/8814a581-1832-4e94-a5df-9e9b6b041507

The Problem

Every time you start a new chat:

You: "Remember that paper on speculative decoding I shared last week?"
Agent: "I don't have access to previous conversations..."
You: *sighs, re-uploads PDF, re-explains context*

You're constantly re-teaching your agent things it should already know.

The Solution

With llm-wiki-kit, your agent maintains its own knowledge base:

You: "What did we learn about speculative decoding?"
Agent: *searches wiki* "Based on the 3 papers you've shared, the Eagle 
architecture shows the best efficiency tradeoffs because..."

The wiki persists. Cross-references build up. Your agent gets smarter with every source you add.

⚡ Quickstart (2 minutes)

1. Install

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

2. Initialize a wiki

mkdir my-research && cd my-research
llm-wiki-kit init --agent claude

3. Connect your agent

Add to Claude Desktop config (claude_desktop_config.json):

{
"mcpServers": {
"llm-wiki-kit": {
"command": "llm-wiki-kit",
"args": ["serve", "--root", "/path/to/my-research"]
}
}
}