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assemblyai-mcp

assemblyai-mcp

by karpovantonme
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

transcribe

Transcribe audio or video from a public URL, with options for speaker labels, chapter summaries, and language detection. Waits for the transcript by default, or returns a job ID for async processing.

Instructions

Transcribe an audio or video file from a URL. Waits for the result by default.

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": {
      "audio_url": "<audio_url>"
    },
    "name": "transcribe"
  }
}

Input Schema

NameRequiredDescriptionDefault
waitNoWait for the transcript to finish. Default true. Set false to get a job id back
audio_urlYesPublic URL of the audio or video file to transcribe
auto_chaptersNoGenerate chapter summaries over the audio
language_codeNoLanguage of the audio, e.g. en_us or de. Omit to let the model detect it
speaker_labelsNoSplit the transcript by speaker. Adds utterances to the result
timeout_secondsNoHow long to wait when wait is true. Default 600

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the disclosure burden. It does reveal a key behavioral trait: it waits for the result by default, which implies async behavior can be opted out of. But it does not explain what happens when wait is false, what the eventual response looks like, or whether a stored transcript is created for later retrieval.

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 short sentences with no wasted words. The core operation is front-loaded, and the key default behavior is stated immediately after. Every sentence earns its place.

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

Completeness2/5

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

There is no output schema and no annotation coverage, yet the tool has six parameters and a potentially long-running async flow. The description does not explain how to retrieve results, what wait=false returns, or how this interacts with sibling transcript tools. This leaves a meaningful gap for correct usage beyond the default path.

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 all six parameters. The description adds no parameter-level detail beyond what the schema provides; even the wait default is already stated in the wait parameter's schema.

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?

The description states a specific verb and resource: transcribe an audio or video file from a URL. This is clear, but it does not explicitly distinguish the tool from siblings like get_transcript or ask_transcript, so it falls short of full differentiation.

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 intended use is implied: call this when you need to transcribe a media file from a URL. However, there are no exclusions or alternatives mentioned, and given the large sibling set, the agent gets no explicit guidance about when to prefer this over transcript retrieval or search tools.

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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