Memtomem MCP server

memtomem

Markdown-first long-term memory for AI coding agents — your files stay yours, and core usage is hook-free by default.

🚧 Alpha — APIs, defaults, and on-disk config surfaces may still change between 0.x releases. Feedback and issue reports are especially welcome: Issues · Discussions.

memtomem turns your markdown notes, documents, and code into a searchable knowledge base that any AI coding agent can use. Write notes as plain .md files — memtomem indexes them and makes them searchable by both keywords and meaning.

flowchart LR
    A["Your files\n.md .json .py"] -->|Index| B["memtomem"]
    B -->|Search| C["AI agent\n(Claude Code, Cursor, etc.)"]

First time here? Follow the Getting Started guide — you'll have a working setup in under 5 minutes. Claude Code or Codex CLI user? See the Korean vibe-coding quickstart.

Why memtomem?

Quick Start

1. Install

uv tool install 'memtomem[all]'       # or: pipx install 'memtomem[all]'
mm --version                          # verify install

[all] bundles the features the sections below describe — ONNX dense embeddings, Korean tokenizer, Ollama / OpenAI providers, code chunker, and the Web UI. For a BM25-only install without those downloads (~40 MB vs ~250 MB), see the minimal install option in the Getting Started guide.

If mm --version shows an older version than the latest release, uv is likely serving cached PyPI metadata — re-run with uv tool install 'memtomem[all]' --refresh, or clear the cache first: uv cache clean memtomem.

mm: command not found? uv tool install drops the shim into ~/.local/bin, which isn't on $PATH in fresh shells on macOS/Linux. Run uv tool update-shell, then open a new shell and re-run mm --version.

2. Setup

Shortened. The full README is on GitHub.