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MCP server mode for montaj — load when running as an MCP client (e.g. Claude Desktop)
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
You MUST use this whenever the user asks for video editing work. Use it when video-related tasks are brought up. Editing, analyzing video, or transcribing videos
Find and download real images from the web — people, logos, brand/event stills, B-roll — to add as overlay image cards or project assets. Load when the prompt asks to source or insert images (e.g. 'add a photo of X', 'find images of the IPO', 'pull a shot of the factory').
Agent-authored workflow task: analyze transcripts across all clips, pick ONE best take per script section, discard all others. Load this when you hit montaj/select_takes in a workflow.
Write a custom JSX overlay component and add it to the project's overlay track.
Agent-authored workflow task: transcribe-and-sample one long-form horizontal source, pick N self-contained clip windows, and fan each out into its own vertical (9:16) clip project with the chosen framing. Load this when you hit montaj/find_clips in a workflow.
The shared vocabulary that domain skills use to name Montaj operations. Domain skills phrase every Montaj interaction as one of these verbs; an interface skill defines how each verb is actually performed. Load this to learn the canonical verbs before authoring or reading a domain skill.
| name | mcp |
| description | MCP server mode for montaj — load when running as an MCP client (e.g. Claude Desktop) |
| step | false |
Montaj exposes itself as an MCP server over stdin/stdout.
montaj mcp
# or directly:
node mcp/server.js
{
"mcpServers": {
"montaj": {
"command": "montaj",
"args": ["mcp"]
}
}
}
Steps are MCP tool calls — not curl, not bash. The MCP host handles transport. Each montaj step is exposed as an MCP tool with the same name and params as the CLI commands.
Follow the headless CLI loop from the root skill. Clips, prompt, and workflow come in via MCP tool call params. Write project state to project.json in the project directory as you go.