| name | clipcannon |
| description | Local-GPU video understanding and editing via MCP — analyse footage, find the best moments, cut highlight reels, add captions, render platform-ready clips (TikTok/Reels/ Shorts/YouTube), clone voices, lip-sync avatars, generate music, and run a real-time voice agent. Use when the user says "edit this video", "find the best moments", "create a highlight reel", "add captions", "clone voice", "lip sync", "render for TikTok", or "talk to Jarvis". Not for plain format conversion (ffmpeg-processing), image generation (comfyui), or meeting capture (echoloop).
|
| version | 0.1.0 |
| author | ChrisRoyse |
| repo | https://github.com/JLMA-Agentic-Ai/jlma-clipcannon |
| mcp_server | true |
| protocol | stdio |
| entry_point | clipcannon serve |
| tags | ["video","editing","voice-cloning","lip-sync","transcription","voice-agent","ai-music","text-to-video","mcp","gpu"] |
| env_vars | ["CLIPCANNON_DATA_DIR","CLIPCANNON_GPU_DEVICE","CLIPCANNON_NVENC"] |
ClipCannon -- AI Video Editor via MCP
Turns Claude into a professional video editor. Ingest video, run a 22-stage AI analysis
DAG, then use 51 MCP tools across 12 categories to find moments, create edits, render
platform-ready clips, generate music, clone voices, produce lip-synced talking-head
videos, and converse via a real-time voice agent. Everything runs locally on GPU with a
tamper-evident SHA-256 provenance chain.
Full catalog (51 tools, 14 ML models, 5 embedding spaces, credit costs, architecture
diagram, Voice Agent lifecycle, integrations) lives in
references/tools-and-models.md. Read it when you need
an exact tool name, a model's VRAM budget, or the credit cost of an operation.
When to Use This Skill
- Video editing: "edit this video", "cut the boring parts", "create a highlight reel"
- Content discovery: "find the most emotional moments", "find where they talk about X"
- Platform rendering: "render for TikTok", "create Instagram Reels version"
- Voice: "clone this speaker's voice", "generate narration", "lip sync"
- Audio: "add background music", "generate sound effects", "compose a score"
- Analysis: "transcribe this video", "who are the speakers?", "scene breakdown"
- Text-to-video: "generate a video from this script" (end-to-end voice + lip-sync)
- Voice Agent: "talk to Jarvis", real-time conversational AI with wake-word activation
When Not to Use
- For simple video format conversion -- use
ffmpeg-processing
- For AI image generation -- use
comfyui or art
- For agentic video production from scratch -- use
open-montage
- For meeting transcription -- use
echoloop
- For audio-only processing -- use
ffmpeg-processing
Quick Path
pip install clipcannon
clipcannon serve
cd config && docker compose up -d
Typical MCP flow once the server is up:
