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Reedapt MCP server

Reedapt MCP server

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by Reedapt
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TypeScript
Hybrid

Dub a video or audio file

dub_media

Upload a local file or public HTTPS link to start dubbing video or audio into chosen languages, preserving voices and background sound; then wait for or fetch results.

Instructions

Uploads a local file (an absolute path) or a public https link, and starts one dub per target language. Returns as soon as the dubs have started; dubbing takes minutes. Then call wait_for_dub or get_dub. Languages the plan can't dub into come back under refused with a reason. Live keys use plan minutes, so confirm the languages with the person first. Test keys dub only video files, and only the first 60 seconds.

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": {
      "source": "<source>",
      "source_language": "<source_language>",
      "target_languages": "<target_languages>"
    },
    "name": "dub_media"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceYesAn absolute path to a local video or audio file, or a public https:// link to one.
metadataNoYour own labels, returned on the dub and in webhooks.
num_speakersNoHow many people speak, if known. Leave out to detect it.
voice_cloningNoKeep each speaker's own voice. Leave out for the account's default.
source_languageYesThe language spoken in the original, as a code such as en, fr or yo.
target_languagesYesCodes from list_languages, such as ["fr-FR", "es-ES"].

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations, it discloses async return timing ('dubbing takes minutes'), partial-failure behavior ('languages the plan can't dub into come back under `refused` with a reason'), billing impact of live keys, and test-key limits (video only, first 60 seconds). These are exactly the behavioral traits an agent needs and none are in the schema or annotations.

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?

Four dense sentences, front-loaded with what it does and the async contract, followed by failure semantics and key-mode caveats. No filler or redundant phrasing.

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 no output schema present, the description still explains the response contract (returns immediately, refused entries with reasons) and timing expectations. Combined with rich schema coverage, nothing material is missing for correct invocation.

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 parameters like source, source_language, and target_languages are already documented. The description restates the 'absolute path or public https link' constraint without adding new syntax or format meaning beyond the schema.

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 states a specific verb and resource ('uploads a local file or public https link, and starts one dub per target language'), making the create-one-dub-per-language semantics explicit. This clearly separates it from sibling read/polling tools like get_dub and wait_for_dub.

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

Usage Guidelines5/5

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

It explicitly names the follow-up alternatives ('Then call wait_for_dub or get_dub') and explains the condition that selects them — the call returns before dubbing finishes. It also gives a precondition ('confirm the languages with the person first') tied to plan-minute consumption.

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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