CutPro

Name: CutPro
Author: getcutpro

getcutpro/mcp

1 repo stars
Updated June 1, 2026
getcutpro/mcp

CutPro is an MCP server that analyzes long videos, creates AI clips, renders them, and publishes through the CutPro API.

About

CutPro MCP wires your agent to CutPro’s video intelligence pipeline so you can analyze long recordings, cut highlight segments, render exports, and publish from tool calls. developers shipping SaaS or content products often have one long demo, podcast, or webinar and need dozens of shorts for X, YouTube Shorts, or TikTok without learning a full edit stack. The server supports local stdio via @cutpro/mcp and a hosted streamable-http endpoint, with authentication through a Pro-plan API key. Treat it as a content accelerator: it does not replace strategy or scripting, but it collapses the mechanical clip-and-export loop so you can iterate on hooks and CTAs faster while your agent stays in the same session.

Analyze long videos, generate clips, render, and publish via CutPro API
npm @cutpro/mcp v1.0.2 with stdio plus remote streamable-http at https://mcp.cut.pro
CUTPRO_API_KEY required (Pro plan; keys at cut.pro/studio/me/api-keys)
Optional CUTPRO_WORKSPACE_ID for multi-workspace keys
GitHub source at getcutpro/mcp

CutPro by the numbers

Data as of Jul 7, 2026 (Skillselion catalog sync)

terminal

claude mcp add --env CUTPRO_API_KEY=YOUR_CUTPRO_API_KEY --env CUTPRO_WORKSPACE_ID=YOUR_CUTPRO_WORKSPACE_ID cutpro -- npx -y @cutpro/mcp

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repo stars	★ 1
Package	@cutpro/mcp
Transport	STDIO, HTTP
Auth	Required
Last updated	June 1, 2026
Repository	getcutpro/mcp ↗

What it does

Turn long-form video into AI-analyzed clips, renders, and publishes through CutPro without manual timeline editing in a separate NLE.

Who is it for?

Best when you record long demos or podcasts and want agent-assisted clipping and publishing on a CutPro Pro plan.

Skip if: Skip if you need frame-perfect cinematic editing or have no long-source video to repurpose.

What you get

Your agent can drive CutPro analyze-clip-render-publish steps so short-form content ships from the same MCP session.

AI-selected clips from long-form video
Rendered clip assets and publish actions via CutPro

By the numbers

2 transports: stdio npm @cutpro/mcp v1.0.2 and remote https://mcp.cut.pro
2 environment variables documented: CUTPRO_API_KEY (required), CUTPRO_WORKSPACE_ID (optional)

README.md

CutPro MCP

A Model Context Protocol (MCP) server that turns long videos into viral clips with AI. It exposes the full CutPro API as tools, so an LLM can run the whole flow: analyze a video, clip the best moments, render the final MP4, and publish to TikTok, Instagram and YouTube.

Key features

End to end. All 34 v1 endpoints as tools: workspace, balance, videos, clipping, clips, templates, renders, posts and connections.
Token efficient. Results are compact and projected to the fields that matter; list_clips is rating sorted, capped, and omits long signed URLs unless asked.
Runs everywhere. stdio for local clients (Claude Code, Cursor, Claude Desktop, Windsurf, VS Code, Cline, Zed) and a hosted Streamable HTTP endpoint with OAuth for ChatGPT and Claude.ai.

Getting started

Requirements

Node.js 18 or newer.
A CutPro account on the Pro plan and an API key. Generate one at cut.pro/studio/me/api-keys.
An MCP-compatible client.

Standard config

Most clients use the same JSON. Add your API key under env:

{
  "mcpServers": {
    "cutpro": {
      "command": "npx",
      "args": ["-y", "@cutpro/mcp"],
      "env": { "CUTPRO_API_KEY": "<your-api-key>" }
    }
  }
}

Install

After installing via a button, add your CUTPRO_API_KEY to the server's env.

Claude Code

claude mcp add cutpro --env CUTPRO_API_KEY=<your-api-key> -- npx -y @cutpro/mcp

Claude Desktop

Add to claude_desktop_config.json (Settings, Developer, Edit Config):

{
  "mcpServers": {
    "cutpro": {
      "command": "npx",
      "args": ["-y", "@cutpro/mcp"],
      "env": { "CUTPRO_API_KEY": "<your-api-key>" }
    }
  }
}

Cursor / Windsurf / VS Code (manual)

Add the standard config above to the client's MCP settings (mcp.json / mcpServers).

Cline

Open the MCP Servers panel, choose Configure, and add the standard config above.

Gemini CLI

gemini mcp add cutpro npx -y @cutpro/mcp -e CUTPRO_API_KEY=<your-api-key>

Codex

Add to ~/.codex/config.toml:

[mcp_servers.cutpro]
command = "npx"
args = ["-y", "@cutpro/mcp"]
env = { "CUTPRO_API_KEY" = "<your-api-key>" }

ChatGPT and Claude.ai (hosted, no install)

Use the hosted server. Add a custom connector pointing to:

https://mcp.cut.pro

You authorize with your CutPro API key on a consent page (OAuth), so no local setup is needed.

Configuration

The server is configured with environment variables.

Variable	Description	Required
`CUTPRO_API_KEY`	Your CutPro API key (Pro plan).	Yes (stdio)
`CUTPRO_WORKSPACE_ID`	Selects the workspace for multi-workspace keys.	No
`CUTPRO_API_URL`	Override the API base URL. Defaults to `https://api.cut.pro/api/v1`.	No

Self-hosting the remote (Streamable HTTP + OAuth)

Variable	Description
`MCP_TRANSPORT=http` / `PORT`	Serve Streamable HTTP at the root instead of stdio.
`MCP_OAUTH=1`	Enable the full OAuth 2.1 layer (discovery, DCR, PKCE) for browser clients.
`MCP_PUBLIC_URL`	Public endpoint, e.g. `https://mcp.cut.pro`. Its origin becomes the OAuth issuer.
`MCP_REDIS_URL`	Back OAuth state with Redis so it survives restarts and scales across instances.

MCP_TRANSPORT=http PORT=8787 MCP_OAUTH=1 \
MCP_PUBLIC_URL=https://mcp.cut.pro MCP_REDIS_URL=redis://127.0.0.1:6379 \
npx -y @cutpro/mcp

In OAuth mode the user authorizes with their own API key on a consent page; the access token maps server side to that key. Without MCP_REDIS_URL, an in-memory store is used (single instance, state lost on restart).

Tools

Workspace and balance

get_workspace: the workspace this key resolved to, with plan and role.
get_balance: current credit balance.
get_balance_history: ledger of credits added and consumed.

Videos and uploads

list_videos: your source video library.
start_upload: get a presigned URL to upload your own file (max 2 GB; .mp4/.mov/.webm/.mkv).
complete_upload: register a finished upload and get its credit cost.
delete_video: delete a source video and its submissions.

Clipping

analyze_video: preview metadata and credit cost of a public URL (free).
submit_clipping: start AI clipping (charges credits).
list_submissions: clipping jobs for a video.
get_submission: poll a submission until completed or failed.
delete_submission: delete a submission and its clips.

Clips and templates

list_clips: clips of a completed submission, rating sorted (URLs opt-in).
apply_template: apply an editing template to clips in bulk.
delete_clip: delete a single clip.
list_templates: editing templates to apply to clips.

Renders

render_clip: render a clip to a final MP4.
get_render: poll a render until completed.
get_render_download: signed download URL of a completed render.
cancel_render: cancel or delete a render.
get_render_limits: render quota for the workspace.
start_bulk_download / get_bulk_download: bundle several renders into one download.

Posts and connections

create_post: publish rendered clips to connected accounts (immediate or scheduled).
list_posts / get_post / update_post / delete_post: manage posts.
publish_post: trigger publishing now.
retry_post_item / delete_post_item: handle individual targets.
list_connections / get_connection: connected social accounts.