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assemblyai-mcp

assemblyai-mcp

by karpovantonme
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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get_subtitles

Retrieve SRT or VTT subtitles from a completed transcript to add captions to your videos. Specify the desired format and optionally set a maximum characters per caption line.

Instructions

Get SRT or VTT subtitles for a completed transcript.

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": {
      "transcript_id": "<transcript_id>",
      "format": "<format>"
    },
    "name": "get_subtitles"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatYesSubtitle format
transcript_idYesId of a completed transcript
chars_per_captionNoMaximum characters per caption line

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the core operation but does not mention error behavior for incomplete transcripts, return format details, permissions, or whether the operation is read-only. For a tool with no annotation coverage, this is a significant gap.

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?

A single, focused sentence that conveys the essential purpose and precondition without redundancy. Every word adds value, and the key constraint ('completed transcript') is front-loaded.

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?

The tool is simple with only three parameters and no output schema. The description covers the operation and precondition, but without annotations or an output schema, it omits details about the exact return value (e.g., raw subtitle text vs. a download URL) and error cases. This is adequate but not fully complete for an agent to predict tool behavior confidently.

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?

The schema already documents all parameters with descriptions (100% coverage), so the baseline is 3. The description adds little beyond the schema, merely reiterating 'SRT or VTT' and 'completed transcript'. The optional chars_per_caption parameter is not mentioned in the description, but the schema handles it adequately.

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 clearly states the verb 'Get', the specific resource 'SRT or VTT subtitles', and the condition 'for a completed transcript'. This distinguishes it from sibling tools like get_transcript and get_speaker_turns, making the tool's purpose unmistakable.

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 clear context by specifying 'for a completed transcript', implying this tool is only appropriate after transcription is done. However, it does not explicitly mention alternatives or when not to use this tool, leaving some inference to the agent.

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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