VideoGenerationMCP

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mix_music_into_video

Mix background music into a video's existing audio, using adaptive loudness to keep music below speech level, with optional ducking while talking.

Instructions

Lay a music bed under a video's existing speech/ambience audio.

Gain is ADAPTIVE by default: both tracks are loudness-measured and the music sits music_below_speech_db LUFS below the speech (14 = clearly audible but secondary; 18-20 = barely-there). duck=true adds a gentle side-chain dip while someone talks. Pass music_gain_db only to force a fixed gain. Music for speech ads is complementary, not the main event. Video stream is copied untouched; inputs may be URLs.

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": {
      "video": "<video>",
      "music": "<music>",
      "output_path": "<output_path>"
    },
    "name": "mix_music_into_video"
  }
}

Input Schema

Name	Required	Description	Default
`duck`	No
`music`	Yes
`video`	Yes
`output_path`	Yes
`music_gain_db`	No
`music_below_speech_db`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description fully discloses key behaviors: adaptive gain, loudness measurement, default ducking behavior, the meaning of LUFS values (14 vs 18-20), how to override with music_gain_db, and that the video stream is copied untouched. This is comprehensive and adds significant value beyond the schema.

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?

The description is about 100 words but every sentence adds meaningful information. It is front-loaded with the core purpose, uses parameter names in backticks for clarity, and avoids filler. The structure follows a logical flow: purpose, default behavior, parameter usage, and special notes.

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?

Given the 6-param complexity, no annotations, and an output schema, the description covers all essential usage aspects: default adaptive gain, ducking, fixed gain override, the purpose of the music bed, and input flexibility (URLs). The existence of an output schema means return values don't need explanation. The description is sufficiently complete for correct selection and invocation.

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

Parameters5/5

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

Schema description coverage is 0%, making this the description's critical burden. It explains music_below_speech_db with concrete LUFS examples, duck as a gentle side-chain dip, and music_gain_db as the fixed-gain override. Even the video/music parameters are clarified by 'inputs may be URLs'. This fully compensates for the lack of schema descriptions.

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?

The description opens with a specific verb+resource: 'Lay a music bed under a video's existing speech/ambience audio.' This precisely distinguishes it from sibling tools like mix_narration (which handles narration) and clearly communicates the tool's function.

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

Usage Guidelines4/5

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

The description provides strong contextual guidance, such as 'Music for speech ads is complementary, not the main event' and explains when to use fixed gain vs adaptive gain. However, it does not explicitly name alternative tools or state when NOT to use this tool, leaving the agent to infer exclusions from the sibling list.

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