ferraus

Name: ferraus
Author: djynnius

by djynniusversion 0.1.4i★ –iRuns on your computer

Registry nameio.github.djynnius/ferraus

Install

Overview

Description from the maker (original English)

Command-line audio workstation: stems, restoration, tuning, sheet music, mastering. JSON everywhere.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ferraus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/djynnius/ferraus:v0.1.4",
        "mcp",
        "serve",
        "--allow",
        "/work"
      ]
    }
  }
}

Run this in your terminal

claude mcp add ferraus -- docker run -i --rm ghcr.io/djynnius/ferraus:v0.1.4 mcp serve --allow /work

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ferraus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/djynnius/ferraus:v0.1.4",
        "mcp",
        "serve",
        "--allow",
        "/work"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ferraus": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/djynnius/ferraus:v0.1.4",
        "mcp",
        "serve",
        "--allow",
        "/work"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account djynnius, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

More stars than 0% of the other 2202 servers in this category
Published to the registry more recently than 97% of the other 2202 servers in this category
Basic checks equal to or better than 100% of the other 2202 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is ferraus safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry yesterday.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

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Claude Real Video

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Let any LLM watch a video locally — and search everything it has ever watched.

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Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

ferraus

A command-line audio workstation for scripts and AI agents.

One cross-platform binary that edits, repairs, separates, tunes, transcribes, notates, and masters audio. Every command returns JSON and records how each file was made, so scripts and agents can chain it without a GUI and reproduce any result. (The *au* is for audio.)

ferraus separate song.mp3                         # vocals, drums, bass, other

ferraus denoise take.wav --auto -o clean.wav # learn the noise, remove it ferraus tune vocal.wav --key auto -o tuned.wav # pitch-correct to the detected key ferraus hum idea.wav --to piano -o idea.piano.wav # humming → MIDI → a real instrument ferraus mix balance stems/*.wav --genre pop # faders that put stems on a genre balance ferraus master mix.wav --target streaming # release-ready master at -14 LUFS

Editing and conversion: convert, trim, cut, split, concat, resample, normalize (EBU R128), channels, silence, tags, waveform and spectrogram export; audio from MP4/MKV/WebM/MOV.
Effects: fades, compressor, limiter, gate, de-esser, multiband, EQ, reverb (plate, FDN, convolution), delay, chorus/flanger/phaser, saturation, vocoder, panning and automation.
Restoration matching Adobe Audition's effects: declip, dehum, declick, dehiss, spectral repair, phase alignment, leveler, scientific filters, and more.
Noise reduction from a noise profile, adaptive, or model-based (DeepFilterNet, RNNoise).
Stem separation in tiers from Demucs to RoFormer ensembles.
Pitch and time: auto-tune, pitch shift with formant preservation, time stretch.
MIDI and notation: quantize, groove, hum-to-MIDI, rendering through SoundFonts, SFZ, or CLAP/VST3 instruments; scores (lead sheet, grand staff, drums, solfa) from audio or MIDI, and sheet-music PDFs performed as audio.
Mixing: stem balance to genre templates, level-aware masking analysis with the EQ cut that fixes it, sidechain ducking, a vocal rider that holds the vocal against the music word by word, dynamic resonance control, song structure (sections, repeats, roles), patching a bad note from a clean repeat, a pass/fail gate before mastering, and whole sessions as cached pipeline files whose stages report their own measurements.
Mastering: one command, or an analyze → plan → verify loop an agent can drive.

For AI agents

Every command takes --json and returns a stable, versioned envelope; ferraus schema prints its JSON Schema; every output gets a provenance sidecar ( .ferraus.json) that ferraus replay reproduces. ferraus is also an MCP server:

claude mcp add ferraus -- ferraus mcp serve --allow ~/music

ferraus describe --agent prints the whole command surface in under 4,000 tokens. See AGENTS.md.

Install the skills

The ferraus skill teaches an agent when and how to use ferraus (the --json contract, dry runs, model downloads). The companion skills carry an engineer's working method for whole jobs: every decision taken from a measurement, every result checked against a numeric gate, and the session delivered as an editable pipeline file plus a report. They are what let an agent mix and master a producer's stems unsupervised.

Skill	What it does
`ferraus`	the CLI contract and the common one-command tasks; routes to the others
`ferraus-mix`	stems → balanced, processed, panned mix with sends, ducking, and a pass/fail gate before mastering
`ferraus-master`	mix → reviewed and verified masters for every destination, deliverables, albums, alternate versions
`ferraus-vocals`	raw take → repaired, tuned, produced vocal; doubles and vocal effects
`ferraus-mix-review`	measured, prioritized notes on a mix or master; reference and version comparisons
`ferraus-stems`	stem export checks, separation, instrumental/a cappella/TV versions, remix prep
`ferraus-beats`	drum patterns, chords, bass lines as DAW-ready MIDI, rendered to audition

Install them with one of:

Agent	Command
Claude Code	`claude plugin marketplace add djynnius/ferraus`, then `claude plugin install ferraus@ferraus` (all skills)
Other agents (Cursor, Codex, Gemini CLI, …)	`npx skills add djynnius/ferraus`, then pick the skills and your agent
Any agent, by hand	copy the folders under `skills/` into the agent's skills folder

The skills drive the ferraus command, so install the CLI first (see Install).

One prompt that sets everything up

To set up an agent, paste this into it:

Install the ferraus CLI and its skill, then use ferraus for any audio, music, or sheet-music task.

Install the CLI if ferraus --version fails. Use one method: macOS or Linux with Homebrew: brew install djynnius/tap/ferraus; otherwise on macOS or Linux: curl -fsSL https://github.com/djynnius/ferraus/releases/latest/download/ferraus-installer.sh | sh; on Windows (PowerShell): powershell -ExecutionPolicy ByPass -c "irm https://github.com/djynnius/ferraus/releases/latest/download/ferraus-installer.ps1 | iex". Then run ferraus doctor --json and confirm "ok": true.
Install the skills. In Claude Code: claude plugin marketplace add djynnius/ferraus, then claude plugin install ferraus@ferraus. In another agent: npx skills add djynnius/ferraus and select all the ferraus skills and your agent. Use one method. You can read the skills directly at https://github.com/djynnius/ferraus/tree/main/skills (the main one, raw: https://raw.githubusercontent.com/djynnius/ferraus/main/skills/ferraus/SKILL.md).
Optional, if you support MCP: register ferraus mcp serve --allow as an MCP server (Claude Code: claude mcp add ferraus -- ferraus mcp serve --allow ~/Music).
Before the first task, run ferraus describe --agent for the command catalog and read https://raw.githubusercontent.com/djynnius/ferraus/main/AGENTS.md for the contract: add --json to every call, plan with --dry-run, never pass --overwrite unless asked, and only download models (-y) when the user agrees.

Examples

examples/ has runnable shell scripts, pipeline files, an MCP client, and a Claude agent loop. They work on test audio that ferraus generates, and CI runs all of them.

Install

Platform	Command
macOS and Linux	`curl -fsSL https://github.com/djynnius/ferraus/releases/latest/download/ferraus-installer.sh \	sh`
Windows (PowerShell)	`powershell -ExecutionPolicy ByPass -c "irm https://github.com/djynnius/ferraus/releases/latest/download/ferraus-installer.ps1 \	iex"`
Homebrew	`brew install djynnius/tap/ferraus`
Debian 13+ / Ubuntu 24.04+	the apt repository below, or the `.deb` from the releases page
Fedora 39+ / RHEL	`sudo curl -fsSLo /etc/yum.repos.d/ferraus.repo https://djynnius.github.io/packages/rpm/ferraus.repo && sudo dnf install ferraus`
Windows (scoop)	`scoop bucket add djynnius https://github.com/djynnius/scoop-bucket; scoop install djynnius/ferraus`
Windows (MSI)	from the releases page
Docker	`docker run --rm -v "$PWD:/work" -v ferraus-data:/data ghcr.io/djynnius/ferraus info song.wav`
From source	`cargo install ferraus`

apt repository (signed; updates arrive with apt upgrade):

sudo mkdir -p /etc/apt/keyrings

sudo curl -fsSLo /etc/apt/keyrings/ferraus-archive-keyring.asc https://djynnius.github.io/packages/ferraus-archive-keyring.asc sudo curl -fsSLo /etc/apt/sources.list.d/ferraus.sources https://djynnius.github.io/packages/apt/ferraus.sources sudo apt update && sudo apt install ferraus

Update: ferraus update --check says whether a newer release is out and how to get it; ferraus update installs it when the release installer put ferraus there, and otherwise prints the Homebrew, apt, dnf, scoop, or cargo command.

Builds: macOS 13.4+ on Apple silicon and Intel; Linux on x86-64 and ARM64, both with glibc 2.38+ (Ubuntu 24.04+, Debian 13+, Fedora 39+) and as a fully static musl build for Alpine and older distributions (the shell installer picks it when glibc is too old; it cannot load CLAP or VST3 plugins); Windows on x86-64 and ARM64 (needs the Microsoft Visual C++ Redistributable, present on most machines). Release artifacts are built and attested only by this repository's GitHub Actions workflows. Model weights are not in the package; they download on first use (with -y or models.auto_download = true) and are verified by SHA-256.

Run ferraus doctor after installing.

Documentation

ferraus docs — the full reference page for any command, offline.
The docs site: https://djynnius.github.io/ferraus (and llms.txt for models).
Product requirements.md), architecture decisions, contributor guide.

License

Apache-2.0 OR MIT, at your option. The score engraving helper (ferraus-engrave) is LGPL-3.0 because it links Verovio; it runs as a separate process.

ferraus

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

ferraus

For AI agents

Install the skills

One prompt that sets everything up

Examples

Install

Documentation

License