MCP server for real-time pitch detection and score alignment. Listens to a singer via microphone and reports their current position in a score and whether they are singing in tune.

What it does

Covers three goals:

Goal 4 — Show the current measure/beat position while singing
Goal 5 — Report pitch accuracy (too high / too low / on pitch)
Goal 6 — Identify where in the score a singer is based on a hummed or sung phrase

Supports both offline analysis of pre-recorded audio and real-time microphone input.

Tools

Tool	Description
`analyze_recording`	Offline: analyse a WAV file against a reference MusicXML score
`load_score`	Load a MusicXML score into a named session; returns a `session_id`
`start_monitoring`	Open the microphone and begin real-time pitch detection
`get_current_position`	Poll the current score position and pitch accuracy
`stop_monitoring`	Stop the microphone and return a session summary
`list_capabilities`	Return server metadata: pitch backend, microphone availability
`health_check`	Check that runtime dependencies (librosa, sounddevice/portaudio) are available

Installation

cd pitch-mcp
uv sync

For real-time monitoring (start_monitoring), PortAudio is required:

# Ubuntu / Debian
sudo apt install libportaudio2

Quick install: on Ubuntu/Debian/Linux Mint, bash install.sh handles uv and the optional libportaudio2 install for you — see SETUP.md for the full non-technical walkthrough. Ready-made client configs (Claude Desktop, Cursor, Windsurf, Continue, Zed) are in examples/. If something goes wrong, check TROUBLESHOOTING.md.

Running

uv run pitch-mcp

Configuration

Variable	Default	Description
`PITCH_BACKEND`	`librosa`	Pitch detection algorithm: `librosa` or `crepe`

crepe requires a manual TensorFlow install (~500 MB) and downloads ~50 MB of model weights on first use. The default librosa backend (pYIN algorithm) works well for singing voice with no extra setup.

Usage examples

// Offline analysis of a recording
{
  "tool": "analyze_recording",
  "arguments": {
    "wav_path": "/path/to/recording.wav",
    "musicxml_path": "/path/to/score.mxl",
    "part_name": "Soprano"
  }
}

// Real-time session
{"tool": "load_score", "arguments": {"musicxml_path": "/path/to/score.mxl", "part_name": "Alto"}}
// → returns {"session_id": "abc123"}

{"tool": "start_monitoring", "arguments": {"session_id": "abc123"}}
{"tool": "get_current_position", "arguments": {"session_id": "abc123"}}
// → returns measure, beat, expected pitch, detected pitch, accuracy

{"tool": "stop_monitoring", "arguments": {"session_id": "abc123"}}

Audio must be 16-bit PCM WAV. MP3 and FLAC are not supported.

Testing

# Unit tests (no microphone or audio required)
VIRTUAL_ENV= .venv/bin/pytest tests/ -v

# Integration tests (offline analysis against a committed fixture pair)
VIRTUAL_ENV= .venv/bin/pytest tests/ -v -m integration

# Manual tests (real microphone required — skip in CI)
VIRTUAL_ENV= .venv/bin/pytest tests/ -v -m manual

112 of the 118 total tests are unit tests, run against mocks and synthetic (in-memory) WAV data — none require real audio hardware or pre-recorded fixtures. The other 6 are marked integration (4 — offline analysis against the committed tests/fixtures/ pair) or manual (2 — full real-microphone session lifecycle) and are excluded from a plain pytest tests/ run by tests/conftest.py; select them explicitly with -m integration / -m manual.

Dependencies

librosa — pYIN pitch detection (primary backend, pure Python)
music21 — score parsing and pitch calculations
sounddevice — real-time microphone input
numpy, scipy — numerics
mcp — MCP protocol

System requirements

Python 3.12+
libportaudio2 — required for real-time microphone input (start_monitoring)
No system libraries required for offline analysis

Phase status

Phase	Status
Phase A — offline analysis	Complete. DTW-based alignment (`dtaidistance`); 112 unit tests plus 4 `-m integration` tests against a committed fixture pair (`tests/fixtures/`)
Phase B — real-time monitoring	Complete. Position tracking is audio-driven (matches detected pitch, not just elapsed time); `tempo_bpm` override supported. Covered by unit tests with mocked `sounddevice`; full-lifecycle `-m manual` tests exist for real-microphone verification but require real hardware to run