babelscribe
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- AlicenseAqualityCmaintenanceEnables MCP clients to transcribe audio/video files locally, generate SRT subtitles, and burn captions into videos via tool calls, without a cloud API.3MIT
- AlicenseNot gradedqualityAmaintenanceProvides local, offline transcription, keyframe extraction, OCR, and pre-publish review of audio, video, and image files, enabling AI agents to see and hear media without cloud or API keys.36 npmApache 2.0
- FlicenseNot gradedqualityCmaintenanceEnables high-performance audio transcription using Faster Whisper with CUDA acceleration, supporting single and batch audio file processing with multiple output formats (VTT, SRT, JSON).-
- AlicenseNot gradedqualityCmaintenanceEnables local transcription of audio/video files and YouTube URLs, generation of SRT/VTT subtitles, and analysis of speech pacing and audience retention risk using faster-whisper.MIT
- AlicenseNot gradedqualityAmaintenanceEnables high-performance, offline transcription of videos from 1000+ platforms and local files using whisper.cpp, with support for multiple model sizes, languages, and output formats over stdio or HTTP.18Apache 2.0
- AlicenseAqualityAmaintenanceEnables AI clients to watch local video files or YouTube/Bilibili and other supported URLs, receiving timestamped transcripts, subtitles, searchable text and keyframe contact sheets. Runs fully offline with local speech recognition and bundled ffmpeg, so no API key or cloud upload is needed.673 PyPI9MIT
TDQS
Scored across 4 tools
Each tool targets a clearly distinct action: list_devices (GPU discovery), list_languages_and_models (model/language info), transcribe (the core operation), and find_media (file discovery). No two tools overlap in purpose, so an agent can select unambiguously.
Consistently snake_case with verb-led names (list_devices, list_languages_and_models, find_media), which is predictable. The lone deviation is 'transcribe', which is verb-only with no noun object, though its meaning is still clear.
Four tools is well-scoped for a transcription server: two read-only discovery helpers, one file-locator helper, and one core action. Nothing feels redundant or missing from the count itself.
The surface covers the full workflow: locate media, inspect devices/models, and transcribe into multiple formats. Minor gaps exist (no batch processing, cancellation, or explicit model-download tool), but agents can work around these.