4 4DA docs
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Install

Download the app

Pre-built binaries — no Rust toolchain required.

Platform Download Auto-updates
Windows .exe installer Yes
macOS .dmg (Apple Silicon & Intel) Yes
Linux .AppImage / .deb Yes

Every release publishes SHASUMS256.txt and per-file .sha256 sidecars so you can verify the binary before you run it. The updater checks GitHub Releases once per session and validates signatures with minisign.

Windows users: SmartScreen prompts on first launch — this is a new application still building reputation, not a warning about the binary. Click More info → Run anyway.

Or run the MCP server

Already using Claude Code, Cursor, or Windsurf? One command gives your AI assistant live vulnerability scanning, dependency health, and ecosystem intelligence:

npx @4da/mcp-server

No API keys. No accounts. No desktop app required. See MCP server & agents.

System requirements

4DA runs on modest hardware. Private, on-device semantic search is built in — no GPU, no API key, and no first-run download required.

Baseline (free) + Cloud AI (BYOK) + Local AI (offline)
RAM 4 GB 4 GB 16 GB (8B model); 32 GB for 12–14B
CPU any 64-bit any 64-bit 6–8 cores
GPU not needed not needed optional (faster)
Disk ~500 MB ~500 MB + 5–9 GB per model

Supported: Windows 10 (1803+) / 11, macOS 10.15+, Ubuntu 22.04+ (WebKitGTK 4.1). Installers are ~30 MB on Windows and macOS; the Linux AppImage is ~112 MB because it bundles its own runtime. The local embedding model ships inside the installer and works fully offline on first run.

Build from source

git clone https://github.com/4DA-Systems/4DA.git
cd 4DA
pnpm install
pnpm tauri dev   # First build: 5–15 min. Dev server: localhost:4444.

Prerequisites: Rust (pinned via rust-toolchain.toml), Node.js 20, pnpm 9.15. Windows also needs VS Build Tools 2022 with the C++ workload.

Next: Quickstart.