manaflow-ai/cmux
cmux
Open source Ghostty-based macOS terminal with vertical tabs and notifications for AI coding agents. Built for multitasking, organization, and programmability.
Usage guide
cmux is an open-source project around amp, claude-code, codex with 23,086 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.
Key features
- Implemented mainly in Swift, useful for judging integration effort in a similar stack.
- GitHub did not detect a repository license, so commercial permission is unconfirmed. Review the repository terms and any model weights, datasets, dependencies, or external services before commercial adoption.
- The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.
Best for
- Evaluating cmux for Swift AI workflows.
- Comparing a GitHub project with 23,086 stars and current repository activity.
Pros
- cmux has visible GitHub traction with 23,086 stars. Topics: amp, claude-code, codex.
- The project provides an external homepage for deeper evaluation.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- No license was detected, so usage risk needs manual review.
Production readiness
cmux should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
GitHub did not report a license, which usually requires manual legal review before production use.
cmux architecture preview
cmux's main path starts at the entry surface, runs through Coding agent runtime, combines OpenAI / Claude / Gemini, Repository context, Shell commands, and returns Code changes / developer feedback.
Entry
CLI / terminal entry
cmux is primarily entered through a developer command or terminal workflow.
brew tap manaflow-ai/cmux
Runtime
Coding agent runtime
The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.
coding workflow
Model
OpenAI / Claude / Gemini
Model calls are likely routed through OpenAI, Claude, Gemini based on README and topic signals.
OpenAI, Claude, Gemini
Context
Repository context
Runtime state, user input, repository files, or configuration provide context for each task.
context signal
Tools
Shell commands
Tool adapters let the runtime act outside the model through Shell commands.
Shell commands
Output
Code changes / developer feedback
The final result is code edits, explanations, repository actions, or developer-facing feedback.
coding output
Featured video
Better Stack
Claude Code + CMUX: The Ultimate AI Coding Terminal
71,508 views · 2026-03-04
Install tutorial
Before you install
- A clean working directory for the first test run
Check the runtime environment
Confirm your system can run a Swift project before starting the installation steps.
Get the project files
Start from the official repository or package so the first run matches the documented behavior.
$ git clone https://github.com/manaflow-ai/cmux.gitInstall or build dependencies
Run the next setup command detected from the project documentation.
$ brew tap manaflow-ai/cmuxAdoption guidance and sources
Practical use cases
Agent workflow prototype
Use it to validate task decomposition, tool calling, memory, tool permissions, and result review loops.
Open source Ghostty-based macOS terminal with vertical tabs and notifi
This is one of the documented reasons to evaluate cmux before choosing a stack.
Focus area: amp
This is one of the documented reasons to evaluate cmux before choosing a stack.
AI Agents project comparison
Compare cmux with similar projects before committing to a stack.
Before adopting
- Complete one clean-environment verification using the official cmux setup path.
- Review repository license, model weights, external services, and dependency terms for your use case.
- Check recent commits, release cadence, issue response, and documentation depth.
- Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.
Configuration notes
- Review README configuration notes before using production data.
Sources checked
These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.
Troubleshooting
- If installation fails, first confirm the command is being run from the README-specified directory.
- If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
- If output looks wrong, return to the smallest documented cmux example before adding complex data.
- For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
- Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is cmux?
cmux is an open-source ai agents project. Open source Ghostty-based macOS terminal with vertical tabs and notifications for AI coding agents. Built for multitasking, organization, and programmability.
How do I install cmux?
Start with the official README. The first detected setup step is: git clone https://github.com/manaflow-ai/cmux.git.
Is cmux beginner-friendly?
If you already know the Swift ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.
Can cmux be used commercially?
GitHub did not detect a repository license, so commercial permission is unconfirmed. Review the repository terms and any model weights, datasets, dependencies, or external services before commercial adoption.
Does cmux need a GPU?
GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.
How should I decide whether to adopt cmux?
Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.