Installation

Requirements

• Python 3.12+
• pip, uv, or pipx
• An embedding provider for semantic search — pick one during mm init (see Embedding Providers below). Fine to skip at first: memtomem works keyword-only until you choose.

LTM Server (memtomem)

uv (recommended)

uv tool install 'memtomem[all]'

pipx

pipx install 'memtomem[all]'

pip

pip install 'memtomem[all]'

[all] is the recommended first install because it matches the main docs: ONNX dense embeddings, Korean tokenizer, Ollama / OpenAI providers, code chunking, the Web UI, Langfuse tracing, and LangGraph Store adapters. For a leaner footprint, drop the extras for a BM25-only install:

uv tool install memtomem                      # no extras — dense search, Web UI, Korean tokenizer unavailable until added

Opt into features later with e.g. uv tool install --reinstall 'memtomem[onnx,web]'.

After installing, verify the binary and upgrade with refreshed package metadata if the version looks stale:

mm --version
uv tool install 'memtomem[all]' --refresh

Optional extras

The extras below are what [all] bundles — install them individually when you want a narrower footprint.

Extra	Description	Command
onnx	fastembed local embeddings (recommended default)	pip install memtomem[onnx]
ollama	Ollama provider client	pip install memtomem[ollama]
openai	OpenAI provider client	pip install memtomem[openai]
korean	kiwipiepy Korean morphological analysis	pip install memtomem[korean]
code	tree-sitter AST chunking (Python / JS / TS)	pip install memtomem[code]
web	FastAPI + uvicorn Web UI	pip install memtomem[web]
langfuse	Langfuse observability tracing	pip install memtomem[langfuse]
langgraph	MemtomemStore and MemtomemBaseStore adapters	pip install memtomem[langgraph]
all	Everything	pip install memtomem[all]

mm CLI

After installation, the commands you’ll reach for most often:

Command	Purpose
mm init	Interactive setup wizard
mm status	Post-install DB / config / embedding health check
mm search <query>	Search the knowledge base
mm add <content>	Add a memory entry
mm web	Launch Web UI dashboard (http://localhost:8080)
mm --version · mm version	Print installed version

Full command list (including ingest, session, context, wiki, watchdog, schedule, tags, upgrade, uninstall): see the CLI Reference.

The MCP server itself ships as the memtomem-server console script. You don’t run it by hand — your MCP client (Claude Desktop, Claude Code, Cursor, etc.) launches it automatically once memtomem is registered in the client’s MCP config. For copy-paste mcpServers JSON per client, see Quick Start → Connect Your MCP Client.

File locations

memtomem keeps everything under your home directory — nothing leaves the machine:

Path	What
~/.memtomem/memtomem.db	SQLite store (chunks + vectors)
~/.memtomem/config.json	LTM configuration written by mm init
~/.memtomem/logs/web.log	Web UI log (from mm web -b)

Override the config directory with the MEMTOMEM_* env vars (see Configuration).

STM Proxy (memtomem-stm)

STM is optional. Install it after the LTM quick-start flow works if you want proactive memory surfacing (presenting relevant memories) or tool-response compression.

uv (recommended)

uv tool install memtomem-stm

pipx

pipx install memtomem-stm

pip

pip install memtomem-stm

uvx (no install)

uvx memtomem-stm --help

For ad-hoc execution only — use uv tool install or another tab for a permanent install with client registration.

Optional extras

Extra	Description	Command
langfuse	Langfuse observability tracing	pip install memtomem-stm[langfuse]
langchain	LangChain agent integration	pip install memtomem-stm[langchain]

mms CLI

After installation, the following commands are available:

Command	Purpose
mms init --mcp claude	First-time setup + auto-register with Claude Code
mms add <name> --command <cmd>	Register an upstream MCP server
mms add --from-clients	Bulk-import upstreams from existing MCP client configs
mms eject <name>	Restore an imported server to its original client and unregister it from STM
mms list	List registered servers (with a SURFACING column)
mms status	Config summary — enabled flag and server count
mms health	Probe upstream connectivity + LTM surfacing readiness
mms --version	Print installed version

The STM proxy itself ships as the memtomem-stm console script. As with LTM, you don’t launch it by hand — once STM is registered with your MCP client (via mms init --mcp claude, mms register, or a .mcp.json entry), the client starts it automatically. STM writes its proxy config to ~/.memtomem/stm_proxy.json; mms add / mms init manage it for you, so you rarely hand-edit it.

Embedding Providers

Provider	Setup	GPU	Cost
ONNX (fastembed)	Built-in	Not required	Free
Ollama	ollama pull nomic-embed-text	Not required	Free
OpenAI	API key required	—	Paid

Not sure which to pick? Start with ONNX — it’s fully local, free, and needs no extra daemon or API key. You can always switch later by re-running mm init or setting MEMTOMEM_EMBEDDING__PROVIDER (note the double underscore — nested pydantic-settings keys use __ as delimiter).

Tech Stack

Category	Technology
MCP	FastMCP (stdio, SSE, Streamable HTTP)
Framework	Pydantic v2, Click (CLI), FastAPI (Web UI)
Database	SQLite (FTS5 full-text search), sqlite-vec (vector search)
Code parsing	tree-sitter (Python, JS, TS AST)
Korean	kiwipiepy morphological analyzer (optional)
Observability	Langfuse (optional)