Turns a song into a multi-track General MIDI file. It works out which instruments are playing, transcribes each one, and names and assigns the tracks, so the result can be practised against in kinesthesia.
Available as a REST API and as MCP tools.
uv sync --extra dev
uv run python -m midifier # API on :8000, docs at /docs
uv run python -m midifier mcp # MCP serverNo configuration is needed to start; results are written to ./data.
# start a transcription
curl -F 'file=@song.mp3' http://localhost:8000/v1/jobs
# {"id":"...","state":"queued"}
# poll it
curl http://localhost:8000/v1/jobs/<id>One job runs at a time, and each takes roughly three times the length of the song, so jobs are
polled rather than waited on. While a job waits, GET /v1/jobs/<id> reports queue_ahead and
eta_seconds, and GET /v1/queue reports how busy the service is. The estimate is measured from
completed jobs rather than configured, so it reflects whatever hardware this runs on.
The OpenAPI schema is at /openapi.json.
The service holds only the hash of an API key, so reading the deployed secret does not let anyone call it. Generate a pair:
uv run python -m midifier keygenDeploy the hash as MIDIFIER_API_KEY_HASH, and give the key to callers. With no hash
configured the service is open, which suits local use.
Callers present the key one of three ways, whichever their client makes easiest:
| caller | how |
|---|---|
| REST | X-API-Key: <key> |
| MCP over HTTP | X-API-Key: <key> or Authorization: Bearer <key> |
| MCP over stdio | the api_key tool argument |
The MCP server is served from the same app at /mcp, so one URL and one key cover both
surfaces, and a job started over MCP is visible over REST.
Every setting is an environment variable prefixed MIDIFIER_. See
.env.example for the full list. The ones that matter:
| variable | default | |
|---|---|---|
MIDIFIER_API_KEY_HASH |
unset | when set, callers must present the key |
MIDIFIER_STORAGE_BACKEND |
local |
local or s3 |
MIDIFIER_MINIO_BUCKET |
— | with the other MINIO_* values, for s3 |
MIDIFIER_MODEL_SIZE |
medium |
small, medium or large |
MIDIFIER_HF_TOKEN |
— | needed to download the transcription weights |
MIDIFIER_MAX_DURATION_SECONDS |
360 |
longest song accepted |
MIDIFIER_MAX_CONCURRENT_JOBS |
1 |
transcriptions run at a time |
uv run pre-commit run --all-files # everything CI runs
uv run pytest --cov # tests, 80% gateConventions and the reasoning behind the pipeline are in AGENTS.md.
MIT. The transcription weights it downloads are licensed separately and are not redistributed here.