whisper-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| transcribeA | Transcribe an audio or video file and return language info + timestamped segments. Args: path: Path to the input audio/video file. model_size: Whisper model size (tiny/base/small/medium/large-v3). device: Inference device: "auto", "cpu", or "cuda". |
| generate_srtA | Transcribe a file and write an .srt subtitle file next to it (or at output_path). Args: path: Path to the input audio/video file. output_path: Where to write the .srt file. Defaults to the input path with a .srt suffix. model_size: Whisper model size (tiny/base/small/medium/large-v3). device: Inference device: "auto", "cpu", or "cuda". |
| burn_captionsA | Burn an existing .srt subtitle file into a video, producing a new video file. Args: video_path: Path to the source video. srt_path: Path to the .srt subtitle file to burn in. output_path: Where to write the captioned video. Defaults to ".captioned". |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
transcribe and generate_srt both involve transcription, but their output types are clearly different: one returns structured segments while the other writes an SRT file. burn_captions is completely distinct, focusing on video rendering rather than audio processing.
generate_srt and burn_captions follow a clear verb_noun pattern. transcribe is a bare verb, which is a minor deviation, but it is still short, predictable, and fits the domain.
Three tools is well-scoped for a whisper-focused server. Each tool covers a meaningful step in the transcription/subtitling workflow without unnecessary redundancy.
The core workflow of transcribing audio, generating subtitles, and burning them into video is fully covered. Minor gaps like explicit plain-text transcript export or translation are absent, but they can be worked around from the timestamped segments.