Mem0 Local (Rust Standalone) v1.0.0

Offline, in-process, long-term memory layer for AI agents — Built 100% in Rust. No Docker. No API keys.

A lightweight standalone implementation of Mem0 designed to run entirely on your local machine. Stores vector embeddings in a plain JSON file and exposes them via CLI, Web Dashboard, or MCP (Model Context Protocol) for AI editor integration.

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✨ Features

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🖥️ System Requirements

To build from source: Requires Rust toolchain (rustup) + windres and ar (from MinGW-w64) in your PATH on Windows.

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🚀 Quick Start

Option 1: Download Pre-built Binary

Download mem0_rust_server.exe from the Releases page and run:

.\mem0_rust_server.exe

The interactive menu will launch. On first use, the embedding model is automatically downloaded from HuggingFace (~90 MB).

Option 2: Use a Local Model (Fully Offline)

Place the model files in a model\ folder next to the .exe:

mem0_rust_server.exe
model\
  model.safetensors
  config.json
  tokenizer.json

The app detects the local model automatically and skips the network download.

Option 3: Build from Source

git clone https://github.com/mem0ai/mem0
cd mem0
cargo build --release
.\target\release\mem0_rust_server.exe

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📁 Data Storage

All memories are stored in:

~/.mem0_rust/db.json

User preferences (language setting) are stored in:

~/.mem0_rust/config.json

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🔧 CLI Reference

# Add a new memory
.\mem0_rust_server.exe add "User prefers Rust for backend development" --user alice

# Semantic search
.\mem0_rust_server.exe search "favorite programming language" --user alice --limit 5

# List all memories for a user
.\mem0_rust_server.exe list --user alice

# Delete a memory by ID
.\mem0_rust_server.exe delete <uuid>

# Clear all memories for a user
.\mem0_rust_server.exe clear --user alice

# Launch Web Dashboard on port 8899
.\mem0_rust_server.exe dashboard --port 8899

# Launch MCP StdIO Server
.\mem0_rust_server.exe mcp

Default --user value: default (used when --user is not specified).

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🌐 Web Dashboard

Launch with:

.\mem0_rust_server.exe dashboard

Then open your browser at: http://localhost:8899

Features:

• View, search, and delete memories in a Glassmorphism UI
• Real-time semantic search
• Dark/Light mode toggle

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🤖 MCP Integration (for AI Editors)

Claude Desktop / Cursor / Windsurf

Add to your MCP config file (e.g., claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "mem0": {
      "command": "C:/path/to/mem0_rust_server.exe",
      "args": ["mcp"]
    }
  }
}

Config file locations:

• Claude Desktop (Windows): %APPDATA%\Claude\claude_desktop_config.json
• Cursor: .cursor/mcp.json in your project root or ~/.cursor/mcp.json globally
• Windsurf: ~/.codeium/windsurf/mcp_config.json

Available MCP Tools

Example MCP Call

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "add_fact",
    "arguments": {
      "fact": "User prefers concise code reviews",
      "user_id": "alice"
    }
  }
}

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🏗️ Architecture

src/
├── main.rs        — CLI entry point, DB path resolution, command routing
├── config.rs      — Language preference persistence
├── db.rs          — JSON flat-file database (load/save)
├── embedding.rs   — Sentence Transformer init + cosine similarity
├── mcp.rs         — StdIO MCP JSON-RPC server (5 tools)
├── dashboard.rs   — Embedded HTTP server + Glassmorphism HTML/CSS/JS UI
└── interactive.rs — Interactive terminal menu (bilingual EN/VI)
build.rs           — Windows resource compiler (icon embedding via windres)

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🔗 References & Credits

• Original Mem0 (Python): mem0ai/mem0
• Embedding Engine: glowrs — Rust Sentence Transformers
• Model: sentence-transformers/all-MiniLM-L6-v2

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📄 License

MIT License — See LICENSE for details.