JOONS LISTEN MCP
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- AlicenseNot gradedqualityAmaintenanceRecords your calls on your own computer, transcribes them on the machine, and lets an agent start, follow, question and annotate a call while it runs. No meeting bot, no account and no cloud; the same core runs as a self-hosted transcription server.20GPL 3.0
- FlicenseAqualityDmaintenanceTranscribes meeting recordings with speaker diarization and automatic speaker identification, leveraging project context to generate minutes. Supports various ASR engines and offers privacy-preserving local processing.14-
- AlicenseAqualityBmaintenanceEnables AI apps to transcribe local audio and video files on the user's own GPU, producing SRT/VTT subtitles and text without cloud uploads. It also helps find media files, list available devices, and list supported languages and models.4206 PyPI8MIT
- AlicenseNot gradedqualityCmaintenanceEnables transcription and speaker diarization of audio files, interviews, and YouTube URLs, producing speaker-attributed transcripts with timestamps. Supports multiple backends (local Whisper, OpenAI API) and output formats (txt, vtt, srt, json).Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables users to start and stop meeting recordings, transcribe audio locally on-device, label speakers, and retrieve full transcripts from desktop AI chat so the assistant can draft meeting minutes, with an included control panel and recording management tools.MIT
- 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).-
TDQS
Scored across 6 tools
Each tool targets a distinct stage of the async pipeline: queue (transcribe/diarize/summarize), poll (status), fetch (result), and inspect (models). The only friction is mild overlap between listen_transcribe's optional minutes flag and listen_summarize, plus status vs result needing the description to clarify state-vs-content. Descriptions do resolve this, so misselection risk is low.
All six tools use a uniform listen_ prefix followed by a clear noun/verb (transcribe, status, diarize, summarize, result, models) in consistent snake_case. The pattern is predictable enough that an agent can guess a tool name before reading it.
Six tools is a tight, well-scoped surface for an asynchronous audio-processing service: one per job type plus the status/result/models trio needed to drive the queue-and-poll workflow. No tool looks redundant or padded.
The lifecycle is largely covered: submit jobs, check status/health, retrieve results in multiple formats, summarize, and inspect engines. Gaps are administrative rather than core — no cancel/delete job, no explicit list-jobs tool (folded into listen_status), and no way to submit remote/uploaded audio, but agents can work around these.