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Statonic MCP

Connects Claude to the Statonic video editor to enable vision-based reference video analysis and AI-driven project authoring. It allows for the direct generation of project variations and automated video structure identification through the Model Context Protocol.

Updated
Feb 25, 2026

Statonic MCP

A Model Context Protocol server that connects Claude to the Statonic video editor, enabling vision-based reference video analysis, AI-driven project authoring, and variation generation from clip library state.

How it works

The server exposes four tools to Claude:

  • get_reference_frames — reads a set of video frames sampled by the editor and returns them as base64 images for vision analysis. Claude identifies the structure of the video (hook, techniques, CTA) and writes the result back via write_reference_result, which the editor picks up via a file watcher and renders into an interactive slot assignment UI.
  • write_statonic_project — writes a complete project JSON to the editor's watched load path. The editor detects the file change and loads the project immediately, allowing Claude to author or modify projects directly.
  • create_variations — reads variation-context.json (written by the editor on session start, containing the current project and filtered clip library) and writes variation JSON files to the variations folder. Each file triggers a live update in the editor's variations panel.

Stack

  • @modelcontextprotocol/sdk for the MCP server transport
  • Anthropic SDK for vision calls within get_reference_frames
  • Node.js fs for file-based communication with the editor process

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