Premiere Pro MCP Server

Normalize Loudness File

normalize_loudness_file

Normalize any audio or video file to a target LUFS with FFmpeg and verify the result using EBU R128, without overwriting the source or an existing output.

Instructions

Create a new loudness-normalized media derivative with FFmpeg, then remeasure that exact output using EBU R128. Never overwrites the input or an existing output file.

Input Schema

TableJSON Schema

Name	Required	Description
`input_path`	Yes	Existing local audio or video file
`output_path`	Yes	New output path; must not already exist
`target_lufs`	No	Integrated loudness target from -70 through -5 LUFS (default: -16)
`tolerance_lu`	No	Post-render integrated-loudness tolerance (default: 1 LU)
`max_true_peak_dbfs`	No	True-peak ceiling from -9 through 0 dBFS (default: -1.5)

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	Whether the tool completed successfully.
`data`	No	Tool-specific result data when ok is true; on failure, diagnostic detail when the tool provides it.
`tool`	Yes	The registered MCP tool name.
`error`	No	Failure detail when ok is false.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.18.6Sep 30, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

changedOutput schema / properties / data / description

Previous value: -"Tool-specific result data when ok is true."New value: +"Tool-specific result data when ok is true; on failure, diagnostic detail when the tool provides it."

Addedv1.14.4Aug 29, 2026

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, so the safety profile is partly given. The description adds real context beyond that: the input and any existing output are never overwritten, and it performs post-render remeasurement of the exact output. It does not state processing time, disk cost, or whether a failed measurement leaves the file behind.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action and followed by the non-destructive guarantee. No filler, every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present to cover return values and 100% schema coverage of all five parameters, the description supplies exactly the missing behavioral context: what it produces, how it verifies, and its non-overwrite guarantee. Nothing needed to call it correctly is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents input_path, output_path, target_lufs, tolerance_lu, and max_true_peak_dbfs with ranges and defaults. The description adds no parameter-level meaning on top of that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Create) and a precise resource (loudness-normalized media derivative), names the engine (FFmpeg) and the standard (EBU R128), and adds the remeasurement step. An agent can distinguish this from analyze_loudness (measurement only) without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the description: call this when you need an actual normalized output file produced and verified. However, it never states when to prefer this over siblings like analyze_loudness or adjust_audio_levels, nor names any alternative or exclusion condition.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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