Voxtract
Related Servers
Alternatives to Voxtract
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceThis service provides fast and reliable transcriptions for audio/video files and voice memos. It allows LLMs to interact with the text content of audio/video file.8MIT
- FlicenseNot gradedqualityBmaintenanceSelf-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.18-
- AlicenseAqualityCmaintenanceLocal speech-to-text transcription using Microsoft's VibeVoice-ASR model with speaker diarization, enabling audio transcription directly in AI tools like Claude Code, Cursor, and OpenCode.33MIT
- AlicenseNot gradedqualityCmaintenanceTranscribes audio/video files, generates summaries and structured knowledge items, and supports Notion integration and chat-based interaction. Works as a standalone CLI, Notion integration, or MCP server tool for agent ecosystems.7 npmMIT
- AlicenseAqualityBmaintenanceEnables AI assistants to transcribe audio and video from URLs or local files with high accuracy, speaker diarization, 119 languages, and word-level timestamps, while also supporting transcription management and caption export in SRT, WebVTT, or plain text.1493 npm13MIT
- AlicenseAqualityCmaintenanceCaptures and transcribes system audio in real-time using OpenAI Whisper, enabling meeting transcription, content creation, and accessibility through natural language.86 npm3MIT
TDQS
Scored across 16 tools
Each tool targets a distinct stage of the transcription workflow: configuration (workdir, context bias, language), staging (inbox, sessions, transcription), and finalization (recordings, transcripts). Even the two transcript readers are clearly differentiated by staging vs finalized context.
Most tools follow a consistent mistral_verb_noun pattern (e.g., get_workdir, set_language, list_sessions). However, transcribe and finalize are bare verbs, and save_processed uses an adjective, which slightly breaks the pattern.
16 tools is just above the typical well-scoped range of 3-15, but each tool earns its place in the transcription pipeline. The count feels slightly heavy but not bloated.
The tool set covers the full lifecycle from inbox to finalized recording, with configuration options and staging review. Minor gaps exist (e.g., no explicit session deletion or transcript editing), but these can be worked around.