Installation

Installation

SuperLocalMemory V3 installs via npm, pip, or git clone. All three methods give you the same product — choose whichever fits your workflow.

No desktop app (DMG/EXE) for V3. V3 is a CLI + MCP server, not a GUI application. The V2 desktop installers are deprecated. Use slm dashboard for the web UI.

Prerequisites

Requirement	Version	Check
Python	3.11+	python3 --version
Node.js (for npm install)	14+	node --version

Python 3.11+ is required for the V3 engine. Node.js is only needed if you install via npm.

---

Method 1: npm (Recommended)

One command installs everything — CLI, Python dependencies, and MCP server.

npm install -g superlocalmemory

This automatically:

• Installs the V3 engine and CLI (slm command)
• Auto-installs Python dependencies (numpy, scipy, networkx, sentence-transformers, torch)
• Creates data directory at ~/.superlocalmemory/
• Detects V2 installations and guides migration

Then set up:

slm setup     # Interactive wizard — choose Mode A/B/C, configure provider
slm warmup    # Pre-download embedding model (~500MB, one-time)

slm warmup is optional. If you skip it, the model downloads automatically on your first slm remember or slm recall.

Verify

slm status

You should see:

SuperLocalMemory V3
  Mode: A
  Provider: none
  Base dir: /home/you/.superlocalmemory
  Database: /home/you/.superlocalmemory/memory.db

---

Method 2: pip

pip install superlocalmemory

Then run:

slm setup
slm warmup    # Optional — pre-download embedding model
slm status    # Verify

---

Method 3: Git Clone (for development or air-gapped environments)

git clone https://github.com/qualixar/superlocalmemory.git
cd superlocalmemory
pip install -e .

Then:

slm setup
slm warmup
slm status

---

What Gets Installed

Component	Size	When
Core math libraries (numpy, scipy, networkx)	~50MB	During install
Search engine (sentence-transformers, einops, torch)	~200MB	During install
Embedding model (nomic-ai/nomic-embed-text-v1.5, 768d)	~500MB	First use or slm warmup

Total disk footprint: ~750MB after first use (mostly PyTorch + embedding model).

RAM usage: ~500-800MB peak during embedding model load, ~20-50MB steady state. CPU-only — no GPU required.

If any dependency fails during install, the installer prints the exact pip install command to fix it. BM25 keyword search works even without embeddings — you're never fully blocked.

---

Platform Notes

macOS (Apple Silicon + Intel)

npm install -g superlocalmemory
slm setup

Works out of the box. Python 3.11+ is included with Homebrew (brew install python@3.12) or available from python.org.

Linux (Ubuntu/Debian/Fedora)

npm install -g superlocalmemory
slm setup

Ensure Python 3.11+ is installed: sudo apt install python3.11 (Ubuntu) or sudo dnf install python3.11 (Fedora).

Windows

npm install -g superlocalmemory
slm setup

Requires Python 3.11+ from python.org. Add Python to PATH during installation.

---

MCP Integration (IDE Setup)

After installing, connect to your AI IDE:

{
  "mcpServers": {
    "superlocalmemory": {
      "command": "slm",
      "args": ["mcp"]
    }
  }
}

Or auto-configure all detected IDEs:

slm connect        # Configure all detected IDEs
slm connect --list # See which IDEs are configured

See IDE Setup for per-IDE instructions.

---

Upgrading from V2

If you have V2 (2.8.6 or earlier) installed:

npm install -g superlocalmemory    # Installs V3 alongside V2
slm migrate                        # Migrates V2 data to V3 schema

V3 is a complete architectural reinvention — new mathematical engine, new retrieval pipeline, new storage schema. Your existing data is preserved. A backup is created automatically before migration.

See Migration from V2 for the full guide.

---

Troubleshooting

slm: command not found

• npm install: Make sure npm global bin is in your PATH. Run npm bin -g to find the location.
• pip install: Make sure Python scripts directory is in your PATH.

ModuleNotFoundError: No module named 'superlocalmemory'

• Ensure Python 3.11+ is the default: python3 --version
• Reinstall: pip install --force-reinstall superlocalmemory

Embedding model fails to download

• Check internet connection
• Try manual warmup: slm warmup
• If behind a proxy, set HTTP_PROXY and HTTPS_PROXY environment variables

Permission errors on macOS/Linux

• Use npm install -g superlocalmemory (not sudo)
• If npm global directory needs permissions: npm config set prefix ~/.npm-global and add ~/.npm-global/bin to PATH

---

Next Steps

• Quick Start Tutorial — Your first memory in 2 minutes
• Modes Explained — Choose between A (zero-cloud), B (local Ollama), C (full power)
• CLI Reference — All 14 commands with examples

---

Part of Qualixar | Created by Varun Pratap Bhardwaj