clipcliper
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CLIPCLIPER_LICENSE_KEY | No | Your Clipcliper license key. Optional; without it, free tier limits apply. |
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 | {} |
| logging | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_transcriptA | Download a public video (YouTube, Twitch VOD, Kick VOD, TikTok) and return its full transcript with timestamps (Whisper large-v3). Asynchronous: if it returns status 'processing', call again with the same url. Results are cached 24 h per url. With a license key it costs one pack minute per started minute of video (minute packs at https://clipcliper.com/mcp; desktop hour packs cost one hour per started hour); without a key, videos up to 15 min (daily limit per IP). |
| get_chaptersA | Split a public video into topic chapters (start/end seconds, title, one-line summary) from its transcript. Transcribes the video first if needed (same cost and async behaviour as get_transcript); the chapters themselves are free and cached. |
| suggest_clipsA | Find the most shareable moments of a public video for short-form clips: start/end seconds aligned to speech, a hook-style title in the video's language and why it works. Transcribes the video first if needed (same cost and async behaviour as get_transcript). Suggestions are free per call. |
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
Each tool has a distinct output: full transcript vs. topic chapters vs. shareable clip suggestions. Overlap in video preprocessing is clearly explained in descriptions, so an agent can reliably select the right tool.
All tool names follow a consistent verb_noun pattern: get_transcript, get_chapters, suggest_clips. The prefix 'get_' versus 'suggest_' matches the action precisely, with no mixed naming styles.
Three tools is a well-scoped set for a video transcription and clip suggestion server. Each tool earns its place and covers a distinct stage of the workflow without redundancy.
The surface covers the core workflow of transcribing a video, generating chapters, and finding clip moments. Minor gaps exist (e.g., no video metadata retrieval or actual clip export), but the primary use case is fully supported.