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Speech-to-text: Whisper transcript with timestamps, Korean and English, optional summary

ai_transcribe

Use when an agent must turn audio into text (meetings, calls, voice notes). Input: POST a file (multipart 'file', raw body, JSON audioBase64) or url; mp3, wav, m4a, ogg, webm, flac, max 25 MB / 10 min. Output: text, language, timestamped segments, word count, duration; summary=true adds summary, key points, action items. $0.006 per started minute (+$0.004 summary), quoted before payment. Not stored. Example: POST {"url":"https://.../call.mp3"} Price: $0.006–$0.064 USDC (Base or Solana) via x402.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ai_transcribe"
  }
}

Input Schema

Name	Required	Description
`url`	No	Public http(s) URL of an audio file (mp3, wav, m4a, ogg, webm, flac; max 25 MB, 10 min)
`summary`	No	Add summary, key points and action items (+$0.004)
`language`	No	Spoken language (default auto-detect)
`audioBase64`	No	Audio bytes as base64 (alternative to url; max 25 MB decoded)

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 6, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations supplied, the description carries the load and does so well: it discloses the 25 MB / 10 min limit, accepted formats, that audio is not stored, that price is quoted before payment, and the payment mechanics (USDC on Base or Solana via x402). It stops short of describing failure modes or timeout behavior, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is front-loaded and information-dense, but pricing is stated twice ("$0.006 per started minute (+$0.004 summary), quoted before payment" and then "Price: $0.006–$0.064 USDC..."), and the inline example plus input/output listings make it read as a packed run-on rather than cleanly separated sections.

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?

There is no output schema, and the description compensates fully by enumerating returned fields (text, language, timestamped segments, word count, duration) and what summary=true adds. Limits, formats, pricing, payment path, and an example call are all present, so an agent has everything needed to invoke it correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline would be 3, but the description adds transport-level meaning the schema lacks: multipart 'file', raw body, or JSON audioBase64 in addition to url. It also ties a cost delta (+$0.004) to the summary flag, which is semantic value 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?

States a specific verb and resource (turn audio into text) up front, and the title plus body make clear it is speech-to-text, distinguishing it from siblings like ai_tts (text-to-speech) and ai_image. An agent can select it without opening the schema.

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?

"Use when an agent must turn audio into text (meetings, calls, voice notes)" gives clear positive context for invocation. It does not name a when-not condition or an alternative sibling, but no obvious overlapping alternative exists in this tool set.

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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