The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Loudcheck listing page.
A loudness compliance verdict, not raw meter output. loudcheck measures
a media file with ffmpeg and answers the question that actually matters —
does this file pass the spec? — against formal published standards:
Agents start here → SKILL.md — when to call this, worked examples, MUST/MUST NOTs. Family contract: FAMILY.md.
measured with the numbers and no judgment)Ships as a CLI and an MCP tool over one engine, so agents and humans get the identical verdict.

An agent (or an engineer) can run ffmpeg's ebur128 filter and get numbers.
What it can't get from a shell is the verdict — that requires knowing the
standard's target, tolerance, and gating, and interpreting integrated
loudness vs. LRA vs. true peak against them. Loudness is one of the most
common causes of delivery rejection, and the gap is not measurement — it's
the standards-aware answer. That's the whole tool.
Requires Python 3.10+ and ffmpeg 5.0+ on PATH.
From a clone: pip install -e ".[mcp,dev]".
Batch mode prints one line per file (plus remediation for fails) and a
summary; --json in batch emits an array. Exit code is 1 if any file
fails.
0 = pass, 1 = fail (non-compliant),
2 = error (missing file, no audio stream, no ffmpeg). Gate a delivery on
the exit code alone.--json is the full contract: overall verdict, per-metric
measured/target/tolerance/delta/pass with the spec citation attached to
every gated metric, failures in plain English, and remediation with the
exact correction — a fail 2.3 LU over target tells you to apply
−2.3 LU gain and hands you the ffmpeg incantation. This tool never applies
the fix (measurement and verdict only); the agent one-shots it with
loudnorm using the delta provided.loudcheck-mcp (stdio; or loudcheck --mcp, or
python -m loudcheck.mcp_server). Zero-install:
uvx --from 'loudcheck[mcp]' loudcheck --mcp. Tools:
check_loudness(path, standard) → same JSON as the CLI, and
list_standards() → the catalog with citations. Verified against
mcp==1.28.1.tool.json at the repo root describes the surface machine-readably —
or fetch it live from any install with loudcheck --schema (the file ships
inside the package; a test keeps the two copies in sync).measurement_context.ffmpeg_version. Minimum supported: 5.0. Developed and
verified against 8.1.Only formal, stable standards live in this repo; per-platform delivery templates (Netflix, DPP, Apple TV+, Amazon, broadcaster specs) never do. Platform specs change unilaterally and cover far more than loudness — the moment they enter, this stops being a near-zero-maintenance community tool and becomes a yearly-maintenance product. If a PR adds a target that a platform can change on its own, it belongs in a separate template layer built on top of this primitive, not here.
Contributions of additional formal standards (e.g. a plain ITU-R BS.1770
mode) are welcome: a standard is pure data in
loudcheck/standards.py — targets, tolerances, and
citations. No code changes required.
One ffmpeg pass with loudnorm=print_format=json (analysis mode) yields
integrated loudness, loudness range, true peak (oversampled dBTP per
BS.1770), and the gating threshold. The test suite cross-checks loudnorm's
reading against ffmpeg's independent ebur128 implementation — the two must
agree within 1 LU for CI to pass, so an ffmpeg release that changes filter
behavior is caught by the suite, not by users.
pytest generates calibrated test tones on the fly (no binaries in the
repo): per BS.1770's calibration statement, a mono 997 Hz sine at 0 dBFS
reads −3.01 LKFS, so tones are generated at exact known loudness — compliant,
too loud, too quiet, and true-peak-hot — and every verdict must match its
known expectation.
Loudness correction (use ffmpeg loudnorm with the delta this tool gives
you) · full-file QC (codec/colour/cadence) · real-time monitoring · GUIs ·
platform delivery templates (see guardrail).
MIT