Point it at a podcast episode. It transcribes with Whisper, finds the best moments, crops to vertical, burns in captions, and spits out TikTok/Shorts/Reels-ready MP4s. Runs locally, no API keys.
No accounts, no cloud processing, no monthly fees. Your files never leave your machine.
Word-level timestamps, speaker diarization. Caches by file hash so re-runs are instant.
OpenCV DNN detects the speaker and keeps them centered in 9:16. Falls back to center crop.
4 styles (branded, hormozi, karaoke, subtle). Synced to word timing, filler words stripped.
Drag in a video, review suggested clips, toggle selections, preview styles, export. All in-browser.
Add to Claude Desktop or Claude Code. Tell it "clip this episode" and it handles the rest.
Auto-picks VideoToolbox on Mac, NVENC on NVIDIA, VAAPI on Linux. CPU fallback works too.
Or use the Web UI if you want to review clips before exporting. Or talk to Claude and let it drive.
Whisper + pyannote for word timestamps and speaker labels
Ranks segments by keyword density, energy peaks, and natural hooks
See clips in the Web UI, adjust timing, pick a caption style
Batch render 1080×1920 MP4s with captions and -14 LUFS audio
Captions get burned into the video at word-level timing. Filler words (um, uh, like) are stripped automatically.
--caption-style brandedDark box on active word. Optional logo. The "safe for any brand" pick.
--caption-style hormoziBold uppercase, yellow highlight. For clips that need to punch.
--caption-style karaokeFull sentence visible, words light up as spoken. Good for storytelling.
--caption-style subtleSmall clean text at the bottom. Stays out of the way.
Add podcli to Claude Desktop or Claude Code. Say "turn this episode into shorts" and it transcribes, analyzes, suggests clips, and exports - all through tool calls. The Web UI updates live as Claude works.
// claude_desktop_config.json { "mcpServers": { "podcli": { "command": "node", "args": ["dist/index.js"], "cwd": "./podcli" } } }
Needs Node ≥ 18, Python ≥ 3.10, FFmpeg. The setup script handles venv, pip, npm install, and model downloads.