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Transcribe from a link

transcribe_url

Start transcribing a media file from a public link (direct file link, YouTube video or Simplecast podcast episode page). Returns job_id and robot_key; then poll get_job.

Input Schema

NameRequiredDescriptionDefault
urlYeshttps:// link to the audio/video file, a YouTube video or a Simplecast episode (…simplecast.com/episodes/… or player.simplecast.com/…).
modelNoDefault "mai-transcribe". See get_service_info.
summaryNoAlso write an AI summary when the transcript is ready.
languageNoISO 639-1 code such as "en". Omit to auto-detect.
robot_keyNoPass the robot_key from your earlier jobs so all your jobs stay together. Omit on your very first call — a new one is returned.
action_itemsNoAlso extract action items when the transcript is ready.
speaker_labelsNoLabel who speaks when.
translate_to_englishNoTranslate the speech to English while transcribing. Only with model "whisper".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / url / description
      Previous value: -"https:// link to the audio/video file or a YouTube video."New value: +"https:// link to the audio/video file, a YouTube video or a Simplecast episode (…simplecast.com/episodes/… or player.simplecast.com/…)."
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-idempotent, open-world call, and the description usefully adds the async job pattern and the job_id/robot_key return values. It says nothing about cost or credit requirements, which matters given the estimate_cost and pay_job siblings, nor about limits or duplicate-job behavior implied by idempotentHint=false.

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, zero waste: what it does and what to do next. The workflow pointer is front-loaded in the second clause.

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

Completeness4/5

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

With no output schema, the description correctly discloses that the call returns job_id and robot_key and how to continue with get_job, which is the minimum an agent needs. The missing piece is the monetization/allocation context hinted at by the pay_job and estimate_cost siblings.

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 in the schema, including the model enum and the robot_key carry-over rule. The description only reinforces the robot_key lifecycle by noting it is returned; baseline 3 applies when the schema does the heavy lifting.

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 ("Start transcribing a media file") and qualifies the source as "a public link", which separates it from transcribe_file. It does not distinguish itself from the sibling start_transcription, so an agent comparing those two still has to infer the difference.

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?

"Returns job_id and robot_key; then poll get_job" gives explicit follow-up guidance and names the sibling to use next. It stops short of stating exclusions (e.g., when to prefer transcribe_file or start_transcription), but the link-vs-file condition is clearly implied.

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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