WhisperCUT v3 — AI-Native Video Factory

AI agents operate as creative directors + editors. One command. One topic. Production-ready TikTok video.

WhisperCUT is an MCP server with 17 tools that automates short-form video production for TikTok, Instagram Reels, and YouTube Shorts. Every creative decision — hooks, pacing, transitions, CTAs — is driven by behavioral science research, not artistic intuition.

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Quick Start (1 command)

Get your wcut_ token from the admin, then run:

curl -sL https://raw.githubusercontent.com/wallpapa/WhisperCUT/main/setup.sh | bash -s YOUR_TOKEN

The script will: verify token, clone, install, build, and configure Claude Code automatically.

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How It Works

Topic + Vibe ──→ WhisperCUT ──→ Production-Ready MP4
                     │
         ┌───────────┼───────────┐
         │           │           │
    Vibe Engine  Hook Scorer  Voice Engine
    (AI Script)  (Gemini/    (MiniMax TTS)
                  Ollama)
         │           │           │
         └───────────┼───────────┘
                     │
              FFmpeg Render
           (1080x1920 @60fps)

5-Hormone Story Arc

Every video follows a neuroscience-backed emotional arc:

Time	Hormone	Purpose	Example
0-3s	Cortisol	Threat/tension hook	"ถ้าลูกคุณอายุ 3 ขวบ อ่านด่วน!"
3-15s	Dopamine	Curiosity gap	"8/10 ครอบครัว ทำสิ่งนี้โดยไม่รู้ตัว"
15-35s	Oxytocin	Trust building	Personal story, vulnerability
35-55s	Adrenaline	Peak moment	Counter-intuitive revelation
55-75s	Serotonin	Resolution + CTA	Actionable advice + save prompt

5 Content Vibes

Vibe	Completion	Share	Best For
educational_warm	71%	6.4%	Expert knowledge sharing
shocking_reveal	74%	8.3%	Myth-busting, bold claims
story_driven	68%	9.1%	Family/child narratives
quick_tips	77%	7.1%	Fast-paced lists
myth_bust	73%	7.6%	"Truth nobody tells you"

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17 MCP Tools

Vibe Engine (v3) — PRIMARY

Tool	Description
whispercut_vibe_edit	One-call video production: topic + vibe → MP4 with script, hook scoring, QA
whispercut_list_vibes	List 5 vibes with predicted completion/share rates

Video Factory (v1)

Tool	Description
whispercut_analyze	Transcribe video with Whisper + AI analysis
whispercut_cut	Generate cut list from analysis
whispercut_caption	Burn animated Thai subtitles via FFmpeg
whispercut_render	Full 9:16 1080x1920 @60fps H.264 render
whispercut_export_capcut	Export timeline as CapCut draft
whispercut_publish	Upload to TikTok via session auth
whispercut_feedback	AI quality scoring + iterative improvement

Style Cloner (v2)

Tool	Description
whispercut_study	Analyze TikTok channel → extract style template
whispercut_clone	Generate script from style template + topic
whispercut_capcut_clone	Export clone script as CapCut draft

Autonomous Agent

Tool	Description
whispercut_run_pipeline	Full pipeline: study → script → QA → voice → render → publish
whispercut_schedule	Add topic to content calendar for scheduled run
whispercut_status	Today's quota, upcoming jobs, recent results

P2P Network

Tool	Description
whispercut_p2p_status	Online workers, credit balance, leaderboard
whispercut_p2p_submit	Submit AI job to distributed network

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P2P Distributed AI Network

Users contribute 20% of their AI processing power to a shared pool. More users = more capacity = better service for everyone.

User A (Gemini)  ←──┐
                     │  Supabase Realtime
User B (Ollama GPU) ←┼──→ Job Queue ←──→ Credit Ledger
                     │
User C (OpenRouter) ←┘

How It Works

1. Your MCP server starts → registers as a worker
2. You do your own work (80%)
3. Network jobs come in → your worker picks up + processes (20%)
4. You earn weighted credits for helping others

Credit System

Job Type	Credits	Weight
hook_score	1	Light — score a hook
weekly_plan	2	Medium — generate content plan
qa_gate	3	Medium — review script quality
vibe_script	5	Heavy — generate full script

New users get 10 free credits on signup.

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BYOK — Bring Your Own Key

Users provide their own AI API key. The system has zero AI costs.

Option A: Gemini Free (Recommended)

AI_PROVIDER=gemini
AI_API_KEY=your-key-from-aistudio.google.com

Get free key: https://aistudio.google.com/apikey (250 req/day)

Option B: Ollama Local (Free Forever)

brew install ollama && ollama pull gemma3:27b && ollama serve

AI_PROVIDER=ollama
AI_MODEL=gemma3:27b

Option C: OpenRouter Free Models

AI_PROVIDER=openrouter
AI_MODEL=google/gemma-3-27b-it:free
AI_API_KEY=sk-or-v1-your-key

Option D: Any OpenAI-Compatible API (GLM, Deepseek, etc.)

AI_PROVIDER=custom
AI_MODEL=glm-4-flash
AI_API_KEY=your-key
AI_BASE_URL=https://open.bigmodel.cn/api/paas/v4/

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Architecture

src/
├── mcp/              # MCP server + 17 tool handlers
│   ├── server.ts     # Main entry (stdio transport, v3.1.0)
│   └── tools/        # One file per tool domain
├── engine/           # Core production engines
│   ├── vibe-engine   # AI script generation (hormone arc)
│   ├── ffmpeg        # Video rendering (1080x1920 @60fps)
│   ├── whisper       # Audio transcription (Thai)
│   ├── voice         # MiniMax TTS (Dr.Gwang clone)
│   ├── timeline      # Timeline composition
│   └── capcut        # CapCut draft export
├── science/          # Behavioral science algorithms
│   ├── hook-scorer   # 6-taxonomy hook evaluation
│   ├── cta-selector  # Conversion-optimized CTA
│   └── vibe-library  # 5 research-encoded vibes
├── ai/               # Unified AI provider (BYOK)
│   ├── provider      # Gemini/OpenRouter/Ollama/Custom gateway
│   ├── prompts       # Prompt templates
│   └── feedback-loop # Auto-improve cycle
├── agent/            # Autonomous orchestration
│   ├── pipeline      # 8-stage production pipeline
│   ├── qa-gate       # Quality gate (7.5/10 threshold)
│   ├── scheduler     # Content calendar + weekly AI plan
│   └── rate-limiter  # Multi-platform quota tracking
├── p2p/              # Distributed AI network
│   ├── worker        # Realtime job processing daemon
│   ├── submitter     # Job submission + fallback
│   └── credits       # Weighted credit system
└── db/               # Supabase client + schema (10 tables)

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Research Foundation

All creative decisions are encoded from peer-reviewed research:

• Dopamine Prediction Error — Schultz et al., 1997
• Narrative Transportation Theory — Green & Brock, 2000
• Fogg Behavior Model — BJ Fogg, 2009
• Zeigarnik Effect — Unresolved tension drives completion
• TikTok Creator Academy — Platform algorithm research (2022-2025)
• 10K+ Video Dataset — Completion rate predictions

Hook Taxonomy (6 types)

Type	Watch-Through Lift
CuriosityGap	+67%
SocialProofShock	+54%
VisualContrast	+48%
DirectAddress	+43%
BoldClaim	+41%
StoryOpening	+38%

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Development

git clone https://github.com/wallpapa/WhisperCUT.git
cd WhisperCUT
npm install
npm run build
npm start          # stdio MCP server
npm run dev        # hot reload
npx tsx test_e2e.ts  # E2E test (8 layers)

Tech Stack

• Runtime: Node.js 22+ / TypeScript (strict, ES2022)
• MCP: @modelcontextprotocol/sdk v1.12.1 (stdio)
• AI: Vercel AI SDK + @ai-sdk/openai-compatible
• Database: Supabase (Postgres + Realtime + Storage)
• Video: FFmpeg (H.264, 1080x1920, 60fps, Thai font)
• TTS: MiniMax (Dr.Gwang cloned voice)

License

MIT