Skip to main content
Glama
Sign In
ffmpeg-mcp-server

ffmpeg-mcp-server

by Ashutos1997
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

normalize_audio

Normalize audio or video loudness to EBU R128 standards, targeting -16 LUFS for podcasts/Reels or -14 LUFS for YouTube, with optional voice clarity filtering.

Instructions

Normalize audio loudness using the broadcast standard EBU R128 (loudnorm). Supports -16 LUFS (podcasts/Reels), -14 LUFS (YouTube), and optional voice clarity enhancement (80Hz high-pass to remove mic rumble). Works on audio or video files.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "inputPath": "<inputPath>",
      "outputPath": "<outputPath>"
    },
    "name": "normalize_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputPathYesPath to the source audio or video file.
outputPathYesDestination path for the normalized media file.
targetLufsNoTarget integrated loudness in LUFS (-16 for podcasts/Reels, -14 for YouTube, -23 for broadcast). Default: -16.
targetPeakDbNoMaximum allowed true peak level in dBTP. Default: -1.5.
voiceClarityNoApply speech enhancement filters (80Hz high-pass to remove mic rumble and gentle compressor for presence). Default: false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the internal filter chain (loudnorm, 80Hz high-pass, compressor), but says nothing about re-encoding, quality impact, whether outputPath is overwritten, or runtime/format constraints. Helpful but incomplete for a file-mutating media operation.

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

Conciseness4/5

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

Three front-loaded sentences with the core function first and the differentiating options after. There is minor redundancy in restating the -16/-14 LUFS targets already in the schema, keeping it below 5.

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

Completeness3/5

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

For a 5-parameter mutation tool with no annotations and no output schema, the description covers the core behavior but omits return values, overwrite semantics, and any failure conditions. An agent can call it, but not predict consequences fully.

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 coverage is 100%, so every parameter is already documented, and the description mostly repeats the schema's own LUFS examples rather than adding new meaning. No extra syntax, units, or interaction guidance (e.g., how targetPeakDb relates to targetLufs) is provided.

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

Purpose4/5

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

States a specific verb and resource ("Normalize audio loudness") plus the underlying method (EBU R128 loudnorm), which clearly separates it from siblings like media_convert or compress_video. It does not explicitly name a sibling it displaces, so 4 rather than 5.

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?

The parenthetical target examples ("-16 LUFS (podcasts/Reels)", "-14 LUFS (YouTube)") imply the intended use cases, but the description never states when to pick this tool over compress_video or media_convert, nor any prerequisites. Usage is inferable but not guided.

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

Deploy Server

Other Tools