Maestri Review: Multi-Agent Coding on an Infinite Canvas

Maestri is a macOS-native multi-agent coding workspace that lets you orchestrate Claude Code, Codex, and other CLI agents on an infinite canvas. It is genuinely novel - no other tool lets you visually wire agents together for direct communication. Best for developers running complex, multi-agent workflows on Apple hardware. Free tier available; Pro at $19/month (as of May 2026).

Quick Verdict

Pros:

• Infinite canvas with visual PTY orchestration between agents is unlike anything else
• Agent-agnostic design works with any CLI-based coding tool
• Ombro on-device AI companion provides useful activity summaries without cloud latency

Cons:

• macOS-only locks out most professional development teams
• Learning curve is steep if you have never worked with multi-agent workflows

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If you are weighing Maestri against single-agent tools, our comparison of Cursor vs GitHub Copilot vs Windsurf covers the leading options for developers who want a more traditional AI coding assistant. Maestri sits in a different category entirely.

What Is Maestri?

Maestri is a native macOS application built around an infinite canvas where each coding agent lives inside its own visual terminal node. You open Maestri's app, create terminal nodes, and drag connection lines between them. Those lines are not decorative. They create real PTY (pseudo-terminal) orchestration pipes that let one agent's output stream directly into another agent's input.

Think of it as a visual programming environment, but instead of connecting code blocks, you are connecting autonomous AI agents. Claude Code can analyze a codebase in one terminal while Codex generates tests in another, and a third agent handles documentation. Maestri routes the relevant context between them so you are not manually copy-pasting outputs.

The app ships with Ombro, an on-device AI companion powered by Apple Intelligence. Ombro watches what your agents are doing, flags potential conflicts (like two agents editing the same file), and generates plain-language summaries of multi-agent activity. Because Ombro runs locally through Apple's frameworks, it adds no cloud latency and your code never leaves your machine for monitoring purposes.

Maestri also includes a markdown notes layer. Agents can read from and write to shared notes on the canvas, creating persistent context that survives between sessions. This is a practical solution to the stateless nature of most CLI agents.

Key Features of Maestri

Maestri's feature set targets a specific workflow: coordinating multiple AI agents on complex projects. Here is what matters.

Infinite Canvas Workspace. The canvas is not a gimmick. It is the core interaction model. You zoom, pan, and organize terminal nodes spatially. In our testing, we arranged agents by responsibility - one cluster for frontend, another for backend, a third for testing. The spatial layout made it easy to track which agents were handling which parts of a project.

PTY Orchestration. This is Maestri's signature feature. Drawing a line between two terminal nodes creates a real PTY pipe. Agent A's stdout becomes Agent B's stdin, filtered through Maestri's context management. During testing, we connected Claude Code (doing code review) to OpenCode (implementing fixes) and the handoff worked without manual intervention about 70% of the time. The other 30% required us to refine the connection parameters.

Ombro AI Companion. Ombro monitors all active agents and generates activity digests. When we had four agents running simultaneously, Ombro caught a conflict where two agents were modifying the same utility file. The summary feature is genuinely useful for keeping track of parallel agent activity, something that gets overwhelming fast without it.

Shared Markdown Notes. Agents can read and write to markdown files pinned on the canvas. We used this to maintain architectural decisions and coding standards that all agents referenced. It solved the "agent amnesia" problem where context disappears between sessions.

Agent-Agnostic Design. Any CLI agent works. We tested with Claude Code, Codex CLI, and OpenCode. If it runs in a terminal, it runs in Maestri. This is a smart architectural decision that future-proofs the app against the rapidly shifting agent landscape.

Maestri Pricing and Plans

Maestri keeps its pricing straightforward. All prices current as of May 2026.

The critical pricing detail: Maestri does not include the agents themselves. You still pay for Claude Code ($20/mo for Max or API costs), Codex (API pricing), or whatever agents you connect. Maestri is the orchestration layer, not the intelligence layer.

For a solo developer running two agents, your real cost is $19/month for Maestri Pro plus $20-40/month for the agents. That is $39-59/month total. Compare that to Cursor's pricing at $20/month for a single integrated agent, and Maestri's value proposition depends entirely on whether multi-agent orchestration saves you enough time to justify 2-3x the cost.

The free tier is genuinely usable for evaluation. Three agent connections let you test the core workflow before committing.

Who Should (and Shouldn't) Use Maestri

Maestri is built for you if:

You are a macOS developer working on projects complex enough to benefit from multiple specialized agents. Think full-stack applications where you want one agent handling React components, another managing API endpoints, and a third writing tests. If you are already using two or more CLI agents and juggling terminal windows, Maestri eliminates that friction.

Solo developers and small teams building ambitious projects get the most value. The spatial organization alone saves meaningful time once you have more than two agents active.

Maestri is not for you if:

You work on Windows or Linux. Full stop. There is no cross-platform version and none announced.

You primarily need inline code completion or single-file editing assistance. Tools like Cursor and GitHub Copilot handle that workflow better because they are embedded in the editor. Maestri operates at a higher abstraction level.

Your team enforces standardized development environments. A macOS-only orchestration tool creates friction in mixed-OS teams. If you need to build workflows your team can automate with AI agents across platforms, check out our guide to automating workflows with AI agents for platform-agnostic approaches.

How Does Maestri Compare to Cursor?

This is the comparison most developers will make, but it is slightly misleading. Maestri and Cursor solve different problems at different layers of the development workflow.

Cursor gives you a single powerful AI agent embedded in your editor. You write code, Cursor suggests completions, refactors functions, and answers questions about your codebase. It is excellent at what it does.

Maestri gives you a control room for multiple agents. You are not editing code directly in Maestri. You are directing agents that edit code in your project directory. The value appears when a single agent is not enough - when you need parallel processing across different concerns.

In our testing, Cursor was faster for focused single-file work. Maestri was faster for coordinating multi-file changes across a full-stack project with three agents running simultaneously. The 70% success rate on automatic agent handoffs means you still intervene regularly, but that is improving with each update.

If you want the deep dive on Cursor specifically, we covered it in our Cursor vs GitHub Copilot vs Windsurf comparison.

Our Testing Process

We tested Maestri over 12 days on a MacBook Pro M3 with macOS 15 Sequoia. Our test project was a Next.js application with a Python FastAPI backend - complex enough to benefit from multi-agent coordination.

We connected Claude Code, Codex CLI, and OpenCode simultaneously. We ran structured test scenarios: coordinated refactoring across frontend and backend, parallel test generation, and documentation updates triggered by code changes.

We measured agent handoff success rate (70% without manual intervention), Ombro conflict detection accuracy (caught 4 out of 5 intentional conflicts we created), and canvas performance with 8+ terminal nodes active (smooth, no lag on M3 hardware).

We did not test the Enterprise tier or shared canvas features. Our evaluation covers solo developer and small team use cases only. Tested May 2026.

The Bottom Line

Maestri occupies a genuinely new category. No other tool lets you visually orchestrate multiple coding agents with real PTY connections on an infinite canvas. If you are a macOS developer already using multiple CLI agents, Maestri eliminates the chaos of juggling terminal windows and manually transferring context.

The 7/10 rating reflects real limitations: macOS-only is a hard constraint, the learning curve is real, and the 70% automatic handoff rate means you are still actively managing agents. But the core concept works, Ombro adds genuine value, and the agent-agnostic design means Maestri gets better as the agents it connects get better.

For developers who want a broader view of AI coding tools, our complete guide to AI agents covers the landscape beyond just coding assistants.

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Frequently Asked Questions

What is Maestri and how does it work?

Maestri is a native macOS app that provides an infinite canvas workspace where you connect multiple coding agents - like Claude Code, Codex, and OpenCode - through visual terminals. You drag lines between terminals to enable direct agent-to-agent communication via PTY orchestration, letting agents collaborate without manual copy-pasting.

Is Maestri free to use?

Maestri offers a free tier for individual developers. A Pro plan runs $19/month and adds features like unlimited agent connections and priority Ombro AI processing. An Enterprise tier is available with custom pricing. You still pay separately for any API-connected agents like Claude Code or Codex (as of May 2026).

Does Maestri work on Windows or Linux?

No. Maestri is macOS-only and requires macOS 14 Sonoma or later. It uses Apple-native frameworks including Metal for canvas rendering and Apple Intelligence for its Ombro companion. There is no Windows, Linux, or web version announced as of May 2026.

What coding agents can Maestri connect to?

Maestri supports Claude Code, OpenAI Codex, OpenCode, and any CLI-based agent that runs in a terminal. You connect agents by opening visual terminal nodes on the canvas and drawing PTY connections between them. The system is agent-agnostic as long as the tool has a command-line interface.

How does Maestri compare to Cursor or GitHub Copilot?

Maestri and Cursor solve different problems. Cursor is a VS Code fork focused on AI-assisted editing inside a single file or project. Maestri orchestrates multiple agents across tasks on an infinite canvas. Maestri is better for complex, multi-agent workflows. Cursor is better for inline code completion and single-agent pairing.

Related AI Coding Agents

• Cursor vs GitHub Copilot vs Windsurf - Head-to-head comparison of the top single-agent coding assistants
• Warp Open-Source (Warp 2.0) - AI-powered terminal that takes a different approach to developer workflows
• Chops - Another coding-focused AI agent worth evaluating
• Bruin - Data pipeline tool with AI agent capabilities

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Editorially reviewed by Todd Stearn. Learn more about how we work.