How do I install the Self Hosted Whisper API skill?

Run npx skillmds@latest add dvcrn/self-hosted-whisper-api in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Self Hosted Whisper API safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Self Hosted Whisper API?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Self Hosted Whisper API free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Self Hosted Whisper API?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Self Hosted Whisper API by dvcrn — Agent Skill

Name: Self Hosted Whisper API
Rating: 4.2 (5 reviews)
Author: dvcrn

Self Hosted Whisper API

Transcribe audio via the self-hosted Whisper ASR instance running on Kubernetes. Use this skill whenever the user wants to transcribe audio files, convert speech to text, generate subtitles, or translate audio. Triggers on audio transcription, speech-to-text, whisper, voice-to-text, subtitle generation, or audio translation requests.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

Self-Hosted Whisper API (curl)

Transcribe an audio file via the Whisper ASR webservice at http://whisper-asr.whisper-asr.svc.cluster.local:9000.

Uses the onerahmet/openai-whisper-asr-webservice API (/asr endpoint).

Quick start

{baseDir}/scripts/transcribe.sh /path/to/audio.m4a

Defaults:

Endpoint: http://whisper-asr.whisper-asr.svc.cluster.local:9000/asr
Task: transcribe
Output: txt

Useful flags

{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --language en --out /tmp/transcript.txt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language de
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output srt --out /tmp/subtitles.srt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output vtt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --translate
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --vad-filter --json
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --word-timestamps --json

Notes

Supported --output formats: txt, json, vtt, srt, tsv
--translate produces an English transcript regardless of source language
--vad-filter enables voice activity detection to skip silent sections
--word-timestamps adds word-level timing (use with --json)
The model is configured on the server side (ASR_MODEL env var), not per request
Swagger docs available at http://whisper-asr.whisper-asr.svc.cluster.local:9000/docs
No authentication required

---name: self-hosted-whisper-apidescription: Transcribe audio via the self-hosted Whisper ASR instance running on Kubernetes. Use this skill whenever the user wants to transcribe audio files, convert speech to text, generate subtitles, or translate audio. Triggers on audio transcription, speech-to-text, whisper, voice-to-text, subtitle generation, or audio translation requests.---# Self-Hosted Whisper API (curl)Transcribe an audio file via the Whisper ASR webservice at `http://whisper-asr.whisper-asr.svc.cluster.local:9000`.Uses the [onerahmet/openai-whisper-asr-webservice](https://github.com/ahmetoner/whisper-asr-webservice) API (`/asr` endpoint).## Quick start```bash{baseDir}/scripts/transcribe.sh /path/to/audio.m4a```Defaults:- Endpoint: `http://whisper-asr.whisper-asr.svc.cluster.local:9000/asr`- Task: `transcribe`- Output: `txt`## Useful flags```bash{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --language en --out /tmp/transcript.txt{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language de{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output srt --out /tmp/subtitles.srt{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --output vtt{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --translate{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --vad-filter --json{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --word-timestamps --json```## Notes- Supported `--output` formats: `txt`, `json`, `vtt`, `srt`, `tsv`- `--translate` produces an English transcript regardless of source language- `--vad-filter` enables voice activity detection to skip silent sections- `--word-timestamps` adds word-level timing (use with `--json`)- The model is configured on the server side (ASR_MODEL env var), not per request- Swagger docs available at `http://whisper-asr.whisper-asr.svc.cluster.local:9000/docs`- No authentication required

Frequently asked questions