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dat-ai-mcp

dat-ai-mcp

by willtholke
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

dat_transcribe

Transcribe audio to text by providing a URL or base64-encoded data. The tool returns the transcribed text.

Instructions

Transcribe audio to text using dat.ai's Whisper API. Provide audio as a URL (the server will fetch it) or as base64-encoded data. Returns transcribed text. Uses sync mode (waits for completion, up to 10 min).

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": "dat_transcribe"
  }
}

Input Schema

NameRequiredDescriptionDefault
asyncNoIf true, return a task_id immediately. Poll with dat_transcribe_status. Default: false.
audio_urlNoURL of the audio file to transcribe. The server will download and transcribe it.
audio_base64NoBase64-encoded audio data. Will be sent as raw bytes.
content_typeNoContent-Type of the audio when using audio_base64, e.g. 'audio/wav', 'audio/mpeg', 'audio/mp4'. Default: 'audio/wav'.audio/wav

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool uses sync mode and waits up to 10 minutes, which is important behavioral info. However, it lacks details on rate limits, authentication requirements, error handling, or what happens on timeout, leaving gaps in transparency.

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?

The description is concise (three sentences) and front-loaded with the core purpose. Each sentence adds essential information without unnecessary elaboration, making it easy for an AI agent to quickly grasp the tool's functionality.

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?

Given the tool has 4 parameters, no output schema, and no annotations, the description covers the key aspects: input methods, sync/async behavior, and timeout. It does not detail the output format beyond 'transcribed text' or error behavior, but for a straightforward transcribe tool, this is largely sufficient.

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 baseline is 3. The description adds value by explaining that audio_url is fetched by the server and audio_base64 is sent as raw bytes, and that async defaults to false. However, it does not provide format or validation details beyond what the schema already describes, so no extra semantic enrichment.

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 tool's purpose: transcribe audio to text using dat.ai's Whisper API. It specifies the two methods of providing audio (URL or base64-encoded data) and distinguishes itself from siblings like dat_transcribe_status for polling, making its role unambiguous.

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 on when to use sync mode (default) vs async mode (by setting async=true and polling with dat_transcribe_status). It also explains the two ways to provide audio input. However, it does not explicitly state when not to use the tool or mention alternatives beyond the sync/async choice.

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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