Local, git-versioned memory for AI coding agents. No RAG, no Docker, no external service. Capture, compile, recall over a local LLM wiki with on-device embeddings and an MCP server.
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LLM Wiki Memory is an MCP server that local, git-versioned memory for AI coding agents. No RAG, no Docker, no external service. Capture, compile, recall over a local LLM wiki with on-device embeddings and an MCP server. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 40/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"llm-wiki-memory": {
"command": "<see-readme>",
"args": []
}
}
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Claude Code, Cursor, Codex, and every other MCP client forget everything when a session ends. LLM Wiki Memory fixes that: it captures your conversations, compiles them into durable project knowledge and lessons your agent applies next time, and recalls the right context through a local MCP server. Memory lives on your machine as plain Markdown in an LLM wiki versioned in git, searched with local embeddings, and consolidated offline while you sleep.
No automated test available for this server. Check the GitHub README for setup instructions.
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Claude Code, Cursor, Codex, and every other MCP client forget everything when a session ends. LLM Wiki Memory fixes that: it captures your conversations, compiles them into durable project knowledge and lessons your agent applies next time, and recalls the right context through a local MCP server. Memory lives on your machine as plain Markdown in an LLM wiki versioned in git, searched with local embeddings, and consolidated offline while you sleep.
No RAG stack. No vector database. No Docker. No cloud. Install with one prompt and your agent never starts from zero again.
Paste this one-liner into your AI coding agent — it covers both a fresh install and an update:
Set up llm-wiki-memory in this project: fetch https://raw.githubusercontent.com/ctxr-dev/llm-wiki-memory/main/AI-INSTALL-PROMPT.md and follow it EXACTLY (it covers fresh install and update; if already installed, the same file is local at @.llm-wiki-memory/src/AI-INSTALL-PROMPT.md).
Or run it yourself — macOS / Linux:
git clone https://github.com/ctxr-dev/llm-wiki-memory ./.llm-wiki-memory/src
./.llm-wiki-memory/src/bootstrap.sh # add --commit-memory to git-track the wiki (you commit it)
./.llm-wiki-memory/src/bootstrap.sh --schedule hourly # recommended: hourly cron / launchd
The --schedule hourly job is recommended, not cosmetic: it is what runs the
gradual embedding warm in the background. Without it (and without a running
webapp daemon) nothing warms ahead of time — recall still self-heals, but each
cold note is embedded inside the first search that touches it.
Windows (PowerShell — the native installer, same flags): bootstrap.ps1 / -CommitMemory / -Schedule hourly.
The bootstrap is idempotent — re-running preserves your .env and rule files.
Full install guide — what bootstrap does (8 steps), Windows prerequisites, updating, non-Claude client registration, and shared team-wiki setup → docs/install.md.
Session to session, your assistant carries your context forward on its own, you stay in control of what gets saved, and everything lives on your machine. How each moment happens: Automatic = no action from you · Agent-led = in its normal flow · Asks first = saves only on your explicit yes · Background = offline housekeeping.
| When you… | What you get | How |
|---|---|---|
| Open a session | It opens already knowing where you left off — a short briefing with your recent notes, in-progress plans + checkbox prog |