leadsheet 0.2.3

Compose simple, playable music with ChatGPT, Claude, Codex, or Gemini — without a DAW, a subscription to a music-generation service, or specialist music software. leadsheet installs a local MCP server and client Skill that turn a natural language prompt into a compact, editable .leadsheet file, then validate and render it as the best available playable audio.

leadsheet

Compose simple, playable music with ChatGPT, Claude, Codex, or Gemini — without a DAW, a subscription to a music-generation service, or specialist music software. leadsheet installs a local MCP server and client Skill that turn a natural language prompt into a compact, editable .leadsheet file, then validate and render it as the best available playable audio.

Version 0.2.0 introduces the .leadsheet format. It is a plain-text, line-oriented music DSL designed for both AI generation and human editing: it is diffable, version-controllable, and substantially cheaper to send through an LLM than verbose JSON or code-based music notation.

Quick Install through an LLM

The easiest installation path is to paste this prompt into your coding assistant or terminal-enabled LLM:

Install and set up the Python package `leadsheet` for me.

1. Prefer `uv tool install leadsheet`; if uv is unavailable, use
   `pip install leadsheet`.
2. Run `leadsheet setup`.
3. Install the recommended external audio dependencies, FluidSynth and
   FFmpeg, using the package manager appropriate for this operating system.
4. Run `leadsheet status` and inspect every line, including the Warnings
   section.
5. If status reports a missing dependency or integration, fix it when safe,
   rerun setup if needed, and run status again.
6. Report exactly what was installed, which client integrations were detected,
   the selected audio backend, and any remaining warnings or commands I need
   to run manually.

Do not modify project files or global client configuration beyond what
`leadsheet setup` is designed to configure. Ask before using a package manager
or making changes outside the normal Leadsheet installation and setup flow.

Usage Examples

After installation, try asking your LLM to compose something simple:

Create a short, happy piano song for me. Make it about 30 seconds long, 
upbeat and cheerful. Use piano and maybe some strings.

Or for something relaxing:

Write me a calm, peaceful piece with a slow tempo. Use soft instruments 
like strings and piano. Make it about a minute long.

Or try something with a beat:

I'd like an upbeat song with drums and bass. Something you'd hear in a 
cafe or lounge. Keep it simple and melodic.

After your LLM creates the .leadsheet file, just ask it to make the song playable and you'll hear the audio.

Manual Installation

uv tool install leadsheet   # recommended
leadsheet setup

or, without uv:

pip install leadsheet
leadsheet setup

leadsheet setup is a required, one-time follow-up step -- pip/wheel installs have no reliable post-install hook, so this is what actually:

• registers the MCP server with every detected client: Claude Code globally (claude mcp add leadsheet -s user), Codex (~/.codex/config.toml), or Gemini (~/.gemini/settings.json)
• installs the Skill for each detected client: ~/.claude/skills/leadsheet/ for Claude Code and ~/.agents/skills/leadsheet/ for Codex
• checks the available audio backend and prints install hints for optional FluidSynth/FFmpeg upgrades
• downloads and caches a General MIDI soundfont for rendering

uv tool install is preferred because it keeps leadsheet in a stable, persistent, isolated environment outside any project venv -- claude mcp add stores an absolute path to the Python interpreter that must keep working long after this install command finishes, so it shouldn't live in a venv you might later delete.

Re-run leadsheet setup any time after upgrading (pip install -U leadsheet / uv tool upgrade leadsheet) to refresh the registered server and the installed skill.

After setup, restart your configured client and ask it to compose something.

AI client support

The server uses the standard MCP protocol over local stdio, so the same .leadsheet workflow works with MCP-enabled clients:

Client	Setup
ChatGPT	Add a local MCP server using command python -m leadsheet.server and the Python interpreter from the leadsheet installation.
Claude Code	Run leadsheet setup; it registers the server and installs the Skill.
Codex	Ensure ~/.codex/config.toml exists, then run leadsheet setup.
Gemini CLI	Ensure ~/.gemini/settings.json exists, then run leadsheet setup.

For ChatGPT, configure the server in the MCP/developer settings of the ChatGPT client you use; the command must point at the same environment where leadsheet was installed. After connecting, ask ChatGPT or Gemini to create a .leadsheet file, call validate, and then call compose.

The .leadsheet format

A file starts with a required tempo line, followed by chord, bass, melody, drum, or custom tracks. The format keeps musical intent visible while factoring out repeated values:

bpm=85 title="Night Drive" key="A minor"

chords "Electric Piano 1" block subdiv=1: Am7 Fmaj7 C G
bass "Electric Bass (finger)" root_fifth oct=2: Am7 Fmaj7 C G
melody "Flute" notes dur=1/4: A4 C5 E5 x2 r E5 C5 A4
drums "Standard" repeat=8: K,H,S,H

Melody is native to the DSL, with a compact notation designed for both AI and human authors. Useful note forms include:

• dur=, int=, and vel= set segment defaults.
• E5@1/2 overrides one note's duration; r is a rest.
• C5+E5+G5 plays a simultaneous-note stack.
• E5 x8 repeats the preceding note, rest, or stack.

Reuse and song structure

Define reusable content once and apply it to multiple tracks. transpose= and vel= are call-site overrides:

define hook notes dur=1/4: E5 G5 A5 x2 G5 E5

melody "Flute" use: hook
melody "Violin" use: hook transpose=-3 vel=70

For a chorus or other multi-track passage, define a section and place it at any bar offset:

section chorus:
  chords "Electric Piano 1" block: Fmaj7 C G Am
  bass "Acoustic Bass" root_fifth oct=2: Fmaj7 C G Am
  drums "Standard" repeat=4: K,H,S,H
  melody "Flute" notes dur=1/4: F5 A5 C5 x2 A5 F5

use section chorus start=8
use section chorus start=24

The full grammar and constraints are in the installed Skill at src/leadsheet/skill/SKILL.md. The examples/ directory contains complete, validated .leadsheet files.

Compose from a .leadsheet file

AI clients normally create and edit the file through the MCP tools. From the command line, the same local server can be started with:

python -m leadsheet.server

The MCP tools are:

• list_capabilities — available chord types, GM instruments, drum kits, styles, and guardrails.
• validate — parses and theory-checks a .leadsheet file without rendering.
• compose — validates, compiles, renders, and saves the best available audio.

After a change, edit the same .leadsheet file and compose it again. The text file is the source of truth.

Audio output

compose selects the best available output automatically:

• FluidSynth + FFmpeg: tagged MP3
• FluidSynth alone: playable WAV
• optional TinySoundFont fallback: playable WAV with no system audio binaries
• no renderer: MIDI output plus an install warning

FluidSynth and FFmpeg are optional but recommended for the highest-fidelity tagged MP3 output:

brew install fluidsynth       # macOS
apt-get install fluidsynth    # Debian/Ubuntu

If either binary is missing, audio does not fail: the server falls back to WAV and includes a warning telling the calling LLM exactly what can be installed to upgrade the result.

To enable the in-process fallback explicitly, install the optional audio extra:

pip install 'leadsheet[audio]'

Other commands

leadsheet status      # what's currently configured
leadsheet uninstall    # remove the MCP registration and skill
leadsheet uninstall --purge-cache   # also delete the cached soundfont

How it works

• Skill (~/.claude/skills/leadsheet/SKILL.md or ~/.agents/skills/leadsheet/SKILL.md): teaches the client a small, explicit schema built around chord symbols ("Am7", "G7sus4") and the .leadsheet text format.
• MCP server (leadsheet.server, stdio transport, registered locally): exposes four tools --
  • list_capabilities -- valid chord types, GM instruments, drum kits/tokens, event styles, and guardrail limits.
  • validate -- structural and music-theory validation, without compiling.
  • compose -- validates, compiles, renders, and returns a playable preview.

Everything is local and stateless: no database, no server-side file storage, no network calls except the one-time soundfont download.

Development

uv sync
uv run pytest

Audio-pipeline tests that need FluidSynth and FFmpeg are skipped automatically if they aren't installed in the dev environment.

License

AGPL-3.0-or-later -- see LICENSE.