whisper-transcribe-mcp
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TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: transcribe_file (local file input), transcribe_base64 (encoded string input), and list_models (metadata/discovery). The file-vs-base64 split is unambiguous because it is keyed to input source, not overlapping functionality.
All three tools follow a consistent snake_case verb_noun pattern (transcribe_file, transcribe_base64, list_models). The convention is predictable and readable throughout.
Three tools is well-scoped for a narrow, single-purpose transcription server; each tool covers a genuinely distinct need (file input, string input, model discovery) with no redundancy.
The core transcribe-and-inspect lifecycle is covered, but common Whisper capabilities like translation, language detection, or alternate output formats (SRT/VTT) are absent. These are minor gaps an agent can work around given the stated purpose.