Mstro App

Browser-based IDE + AI agent orchestration CLI. Run Claude Code in parallel across git worktrees, auto-approve safe tools with the Security Bouncer, and control long-running AI work from any device at mstro.app.

Free for the first 1,000 users. No credit card. Bring your own Anthropic API key.

Start in 30 seconds:

curl -fsSL install.mstro.app | sh

Then run mstro in any project directory. Open mstro.app. Start building.

What Mstro Does

1. Browser-based IDE for remote machines

Open mstro.app and connect to Claude Code running on your laptop, cloud VMs, or servers. Chat, edit files, use git, run terminals. All from any browser, on any device. Your code stays on your hardware.

2. Long-running AI tasks without babysitting

Start a complex task and walk away. The Security Bouncer handles every permission decision automatically. A three-layer watchdog detects stalls, kills frozen processes, and recovers. Come back to finished work.

3. One prompt to a full kanban board of parallel AI agents

Describe what you want. The PM board breaks it into a kanban board of tasks, then AI agent teams execute them in parallel on separate git worktrees. Track progress in real time. What takes a solo developer a week ships in hours.

4. One prompt to an autonomous business

The long-term direction: self-managing AI-powered businesses that optimize for profit. Today Mstro ships the agent orchestration layer that makes it possible.

Quick Start

Prerequisites:

• Node.js 18+ (check with node --version, download here)
• Claude Code installed and signed in. claude must work in your terminal

Install:

curl -fsSL install.mstro.app | sh

The installer detects bun, pnpm, or npm and installs the CLI globally. Or with npm directly:

npm install -g mstro-app

Then run the CLI in any project directory:

mstro

On first run, mstro opens your browser to sign in. Once connected, open mstro.app — your machine appears as a workspace.

Run mstro on multiple machines. Each one appears as a separate workspace.

Stop with Ctrl+C.

How It Works

Browser (mstro.app) <--WS--> Platform Server (relay) <--WS--> mstro CLI (your machine) --> Claude Code

Your code never leaves your computer. The browser is a window into what's happening on your machines.

Features

Feature	What it does
Chat	Parallel AI conversation tabs with file autocomplete and drag-and-drop context
PM Board	One prompt becomes a kanban board. AI agent teams build features in parallel on separate git worktrees
Quality	Automated linting, complexity analysis, and AI code review before shipping
Files	Browse, edit, search, and diff files on any connected machine with syntax highlighting
Git	Stage, commit, push, and create PRs — AI writes commit messages
Terminal	Full PTY shell access to any machine from your browser
Shared Apps	Invite others with view-only, project control, or full machine access

Security

The Security Bouncer makes permission decisions so you don't have to sit there clicking "Allow."

Two layers:

1. Pattern matching (<5ms): instantly blocks known threats like rm -rf / and reverse shells
2. AI analysis (~200-500ms): catches prompt injection and data exfiltration

Validated against 400+ tests covering 22 MITRE ATT&CK techniques.

For the full architecture, threat model, red-team results, and vulnerability reporting, see SECURITY.md.

Autonomous Execution

Three safety layers run continuously during AI sessions:

• Security Bouncer: 2-layer tool approval (pattern matching + Haiku AI) via MCP
• Stall Assessor: heuristic + AI analysis detects stuck processes
• Tool Watchdog: per-tool adaptive timeouts using RFC 6298 EMA, with custom profiles for long-running operations (WebFetch 3m, Bash 5m, Task 15m)

PM Board

The PM board turns a single prompt into a managed project:

1. Describe what you want to build
2. AI generates a kanban board with prioritized issues
3. AI agent teams execute issues in parallel on separate git worktrees
4. Track progress in real time — see each agent's output, status, and artifacts
5. Review quality before merging

Configurable parallel execution (max concurrent agents), custom review criteria per board, and board-scoped artifacts (progress logs, output files, review results).

Custom Review Agents

When a task moves to "In Review", an AI review agent checks the work. There are three built-in agents:

Agent	When used	What it checks
review-code	Task modifies source files	Acceptance criteria, bugs, security, code quality
review-quality	Task produces non-code output	Acceptance criteria, content accuracy, completeness, structure
review-custom	Board has custom review criteria	Acceptance criteria + your custom criteria

Quick customization. Click the gear icon on the "In Review" column header to set review criteria for the board. Works for code, writing, research, design, whatever.

Full prompt control. Drop a markdown agent file into your board's agents/ directory to replace the default review prompt entirely:

.mstro/pm/boards/BOARD-001/
  board.md
  agents/
    review-code.md      # Override code review for this board
    review-quality.md   # Override non-code review for this board
    review-custom.md    # Override custom criteria review for this board

Agent files are markdown with YAML frontmatter and {{variable}} placeholders:

---
name: review-code
description: Custom code review for my project
type: review
variables: [issue_id, issue_title, files_modified, acceptance_criteria, output_path]
checks: [criteria_met, code_quality, no_obvious_bugs]
---

You are a reviewer for {{issue_title}}.

## Files Modified
{{files_modified}}

## Acceptance Criteria
{{acceptance_criteria}}

(your custom instructions here)

Output EXACTLY one JSON object on its own line (no markdown fencing):
{"passed": true, "checks": [{"name": "criteria_met", "passed": true, "details": "..."}]}

Variables you can use:

Variable	Available in	Description
issue_id	All agents	Issue ID (e.g., ISS-001)
issue_title	All agents	Issue title
acceptance_criteria	All agents	Formatted acceptance criteria checklist
files_modified	review-code	List of modified file paths
output_path	review-code, review-quality	Path to output artifact
issue_spec_path	review-quality	Path to the issue spec file
context_section	review-custom	Files or output section (depends on task type)
review_criteria	review-custom	Board-level review criteria text
read_instruction	review-custom	Read instruction (changes based on task type)

Resolution order: board agent file > system default > hardcoded fallback. If there's no board override, the built-in agents run.

Quality

Quality analysis runs across your codebase:

• Tool detection: auto-detects linters and analyzers for your ecosystem (Node, Python, Rust, Go, Swift, Kotlin)
• Automated scanning: runs detected tools with progress tracking
• AI code review: Claude reviews code for architecture violations, SOLID principles, security, and performance
• Severity scoring: findings tagged with severity, category, file paths, and line numbers
• Automated fixes: AI can fix identified issues with progress tracking

CLI Reference

mstro                       # Start (auto-authenticates)
mstro login                 # Authenticate or switch accounts
mstro logout                # Sign out
mstro whoami                # Show user and device info
mstro status                # Show connection status
mstro setup-terminal        # Enable web terminal (compiles native module)
mstro telemetry [on|off]    # Toggle anonymous telemetry

Options

Flag	Description
-p, --port <port>	Start on a specific port (default: 4101, auto-increments if busy)
-w, --working-dir <dir>	Set working directory
-v, --verbose	Verbose output
--version	Show version
--help	Show help

Configuration

Environment Variables

Variable	Description
PORT	Override server port
BOUNCER_USE_AI	false to disable AI analysis layer
MSTRO_TELEMETRY	0 to disable telemetry

Config Files

Stored in ~/.mstro/:

File	Purpose
credentials.json	Device auth token (created by mstro login)
settings.json	Model selection, preferences
session-registry.json	Tab-to-session mapping

Architecture

server/
  index.ts                          # Hono app entry, port detection, WebSocket setup
  services/
    websocket/handler.ts            # Main WebSocket message router
    websocket/*-handlers.ts         # Domain handlers (session, plan, quality, git, terminal, files)
    plan/executor.ts                # PM board execution engine
    plan/composer.ts                # AI prompt composition for boards
    plan/review-gate.ts             # Quality gates for board execution
    plan/agent-loader.ts            # Review agent prompt loader (layered resolution)
    plan/agents/                    # System default review agent prompts (markdown)
    terminal/pty-manager.ts         # PTY session management
    platform.ts                     # WebSocket connection to platform server
  cli/
    headless/runner.ts              # Claude Code orchestrator
    headless/stall-assessor.ts      # 2-layer stall detection (heuristic + Haiku AI)
    headless/tool-watchdog.ts       # Per-tool adaptive timeouts (RFC 6298 EMA)
    improvisation-session-manager.ts # Session orchestration, retry, checkpoints
  mcp/
    server.ts                       # MCP server (stdio transport)
    bouncer-integration.ts          # 2-layer security (patterns + Haiku AI)
    security-patterns.ts            # Threat/safe pattern matching
bin/
  mstro.js                          # CLI entry point
  commands/                         # login, logout, status, whoami, config

Key Subsystems

• Headless Runner: spawns Claude Code processes with MCP bouncer integration, manages lifecycle
• Improvisation Session Manager: session orchestration, retry with context recovery, checkpoint-and-retry on tool timeouts
• Security Bouncer: MCP-integrated 2-layer tool approval (see SECURITY.md)
• PM Board Executor: parallel board execution with wave-based scheduling and quality gates
• PTY Manager: terminal session management with tmux support and subscriber model
• Session Registry: tab-to-session persistence across WebSocket disconnects

Optional Setup

Web Terminal

The terminal tab requires a native module. Mstro tries to compile it automatically on first run. If it fails, install build tools first:

• macOS: xcode-select --install
• Linux (Debian/Ubuntu): sudo apt install build-essential python3
• Linux (Fedora/RHEL): sudo dnf install gcc-c++ make python3
• Windows: npm install -g windows-build-tools

Then run mstro setup-terminal.

Persistent Terminals

Install tmux for sessions that survive restarts:

# macOS
brew install tmux
# Debian/Ubuntu
sudo apt install tmux

Development

cd cli
npm install
npm run dev          # Dev server with tsx (port 4101)
npm run test         # vitest
npm run check        # tsc + vitest + biome + npm audit
npm run build        # tsc -p tsconfig.build.json

The CLI runs on Node.js with tsx in development (no build step). Hono serves HTTP and WebSocket. Biome handles linting. Published as ESM.

Troubleshooting

Problem	Fix
claude not found	Install Claude Code and sign in
Port conflict	mstro -p 4200 or let it auto-increment
Machine not appearing	Run mstro status to verify connection
node-pty build fails	Install build tools (see Optional Setup), then mstro setup-terminal

Uninstall

npm uninstall -g mstro-app
rm -rf ~/.mstro

Links

• Web App: mstro.app
• Blog: mstro.app/blog — essays on AI agent orchestration, parallel agents, and shipping with Claude Code
• Compare: mstro.app/compare — how Mstro compares to Cursor, Claude Code, Copilot, Codex, JetBrains, and more
• Security: SECURITY.md — bouncer architecture, threat model, red teaming, vulnerability reporting

License

MIT