A
licenseNot graded
qualityD
maintenanceEnables AI assistants to download YouTube videos and transcribe them locally using OpenAI's Whisper speech recognition model.
MIT
Video to Text MCP Server
by strzhao
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TDQS
B3.2/5.0
Scored across 2 tools
Disambiguation4/5
The two tools have distinct primary purposes: video_to_text handles video files with audio extraction, while voice_to_text handles audio files directly. However, there is some functional overlap in the transcription step, which could cause minor confusion if an agent needs to transcribe audio from a video but chooses the wrong tool. The descriptions help clarify the difference.
Naming Consistency5/5
Both tools follow a consistent snake_case naming pattern with a clear 'source_to_text' structure (video_to_text and voice_to_text). This makes them predictable and easy to understand, with no deviations in style or convention across the set.
Tool Count3/5
With only 2 tools, the server feels thin for a video-to-text domain, as it lacks operations for managing transcripts (e.g., editing, saving in different formats) or handling video/audio metadata. While the core functionality is covered, the set is borderline minimal and may limit agent workflows.
Completeness3/5
The tools cover the basic transcription process from video and audio sources, but there are notable gaps: no tools for updating, deleting, or listing transcripts, and no support for batch processing or different output formats. This could lead to dead ends in more complex agent tasks, though simple transcription needs are met.
Maintenance
ActivityInactive
ResponsivenessNo issues