Montaj

A video editing CLIP for AI agents. CLI-first, agent-native, open source.

Montaj is a CLIP — a CLI Program for agents. It clips onto your existing AI agent (Claude Code, OpenClaw, Cursor, or any harness) and gives it the specialized tools to edit video. Built-in steps cover the full editing pipeline. The agent decides what to run, in what order, and with what parameters.

The fundamental dependency is an agent. Montaj doesn't edit on its own. It provides the tools; the agent makes the creative decisions.

Quick install

Send this to your agent:

Install Montaj from https://github.com/theSamPadilla/montaj, then read skills/onboarding/SKILL.md to get us started.

Install

PyPI:

pip install montaj
# install Node.js >=18 separately: https://nodejs.org
montaj install whisper   # whisper-cpp binary + model weights
montaj install ui        # npm deps + UI build

Homebrew (macOS) — installs Node.js and all Python deps:

brew install theSamPadilla/montaj/montaj
montaj install ffmpeg   # pinned static ffmpeg/ffprobe (with zscale for HDR); also in `install all`

From source:

git clone https://github.com/theSamPadilla/montaj
cd montaj
pip install -e ".[connectors]"
montaj install whisper
montaj install ui

Optional extras:

pip install "montaj[connectors]"  # Kling, Gemini, OpenAI API connectors
pip install "montaj[rvm]"         # background removal (torch + RVM)
pip install "montaj[demucs]"      # audio stem separation
montaj install all                # whisper + ui + rvm

Quick Start

# Headless — agent edits, renders, done
montaj run ./clips --prompt "tight cuts, remove filler, 9:16"

# With UI — watch the agent work live, tweak the result
montaj serve

# AI video generation — agent creates from a text prompt via Kling
montaj serve   # then create an ai_video project in the UI

What's Inside

steps/              Step executables + JSON schemas (probe, trim, transcribe, generate, etc.)
workflows/          Editing plans (clean_cut, overlays, ai_video, lyrics_video, etc.)
skills/             Agent skill contracts (onboarding, edit-session, ai-video-plan, ai-video-generate, etc.)
connectors/         API connectors (Kling, Gemini, OpenAI)

render/             React + Puppeteer + ffmpeg render engine
serve/              Local HTTP + SSE server (montaj serve)
ui/                 Browser UI (Vite + React + Tailwind)
docs/               Architecture, CLI reference, UI design, schemas

How It Works

1. Upload clips + write an editing prompt (or describe an AI video)
2. montaj creates project.json [pending]
3. Agent picks it up, reads the workflow, calls steps as tools
4. Agent writes project.json as it works → UI updates live via SSE
5. Agent marks project [draft]
6. Human reviews in browser (optional) → tweaks → marks [final]
7. Render engine → final MP4

CLI

Every operation is available from the terminal. montaj is the full command, mtj is the short alias.

montaj run ./clips --prompt "tight cuts, upbeat pacing"
montaj serve
montaj render
montaj fetch https://youtube.com/watch?v=...

See the CLI Reference for the full documentation.

Steps & Workflows

Steps are individual editing operations — Python executables with JSON schemas, callable as agent tools, CLI commands, or API calls. Native steps ship with Montaj; custom steps are any executable that follows the output convention.

Workflows are suggested editing plans — which steps to use and with what default params. The agent reads the plan, reads the prompt, and decides the actual execution.

Custom steps and workflows are discovered automatically — no registration needed. See the Steps Reference and Core Concepts for details.

Skills

Skills are agent-readable contracts that teach the agent how to approach a specific editing task. Each skill describes the goal, the steps to use, the parameter choices, and the quality criteria.

Available skills: onboarding, edit-session, ai-video-plan, ai-video-generate, eval-scenes, overlay, write-overlay, animation-sections, lyrics-video, style-profile, serve, parallel, select-takes, waveform-silence, camera-vocabulary, workflow-builder, mcp.

Connectors

API connectors for external services. Installed via pip install "montaj[connectors]".

Render Engine

React + Puppeteer + ffmpeg. Reads project.json [final], renders captions and overlays frame-by-frame via headless Chrome, composites with source footage via ffmpeg → final MP4.

See the Render Engine docs for the full breakdown.

UI

Optional browser interface. Upload → watch the agent work live → review → render.

montaj serve   # http://localhost:3000

• Editor — timeline, preview player, caption editor, overlay editor
• Storyboard — AI video scene planning with image/style references
• Workflows — n8n-style node graph for building editing plans
• Overlays — live animated preview of custom JSX overlays
• Profiles — view creator style profiles (pacing, color palette, editorial direction)

The UI is a layer on top of the CLI, not a separate system. Every action maps to a CLI command.

Project JSON

The single format that flows through the entire pipeline. One file, three states:

For AI video projects, the storyboard (scenes, image refs, style refs) lives inside the same project.json.

See the Core Concepts page and docs/schemas/project.md for the full schema.

Docs

Full documentation at docs.montaj.ag:

• Installation — Homebrew, PyPI, source
• Quick Start — first project in 2 minutes
• CLI Reference — full command list
• Steps Reference — all 27+ built-in steps
• Core Concepts — architecture, project.json, trim specs, workflows
• Render Engine — the compositing pipeline
• Agent Integration — MCP, HTTP API, skills
• Connectors — Kling, Gemini, OpenAI setup
• Extending — custom steps, workflows, connectors

Internal references (for contributors):

• Architecture — deep implementation details
• Project JSON Schema — field-level schema reference
• Overlay Contract — render component spec

License

MIT — do whatever you want. See LICENSE.