video-toolkit-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DEBUG | No | Enable debug logging | 0 |
| FFMPEG_PATH | No | Path to ffmpeg binary | ffmpeg |
| YT_DLP_PATH | No | Path to yt-dlp binary | yt-dlp |
| OPENAI_API_KEY | No | OpenAI API key for Whisper-based subtitle generation | |
| WHISPER_MODEL_PATH | No | Path to whisper model (for local whisper) | Auto-download |
| WHISPER_BINARY_PATH | No | Path to local whisper binary | whisper |
| VIDEO_TOOLKIT_STORAGE_DIR | No | Default directory for downloaded videos | ~/.video-toolkit/downloads |
| VIDEO_TOOLKIT_WHISPER_ENGINE | No | Preferred whisper engine: openai, local, or auto | auto |
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get-transcriptB | Retrieve the transcript of a video from supported platforms (YouTube, Bilibili, Vimeo, etc.). Accepts various URL formats and returns the full transcript with timestamps. |
| list-transcript-languagesA | List all available transcript languages for a video from any supported platform. |
| download-videoA | Download a video from any supported platform (YouTube, Vimeo, etc.) to local storage. Returns the file path of the downloaded video. |
| list-downloadsA | List all downloaded video files in the storage directory or a specified directory. |
| generate-subtitlesA | Generate subtitles for a local video file using AI speech-to-text (OpenAI Whisper or local whisper). Creates an SRT or VTT file alongside the video. |
| transcribe-audioA | Transcribes audio via Whisper. Preferred: audio_url (most token-efficient; server fetches bytes). audio_base64 is for small clips only (<= ~60KB raw per call). audio_path only works when the MCP host shares a filesystem with the caller (often false on Claude.ai / Claude Code). For larger payloads in sandboxed environments, use transcribe_upload_start / transcribe_upload_append / transcribe_upload_finalize. Server re-encodes to Opus 16kHz mono 16kbps before Whisper unless skip_compression=true. Long audio (>5min) or async=true returns a job_id; poll transcribe_get_job. |
| transcribe_upload_startA | Begin a chunked audio upload for large payloads. Returns upload_id and max_chunk_bytes (~60KB). |
| transcribe_upload_appendC | Append one base64 chunk to an upload session. |
| transcribe_upload_finalizeB | Finalize a chunked upload, run compression + Whisper, return structured JSON (or text with as_text). |
| transcribe_get_jobC | Poll an async transcription job created by transcribe-audio. |
| transcribe_cancel_jobC | Cancel an async transcription job (best-effort). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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