CutPro MCP

by getcutpro

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About

34-tool MCP server for CutPro's v1 API — analyze videos, clip, render, and publish posts via AI clients like Claude, ChatGPT, and Cursor.

Details

Author
getcutpro
GitHub stars
1
Downloads
351
Categories
Other, API, Media, Marketing, Developer Tools, AI

- End‑to‑end coverage of all 34 CutPro API tools.
- Token‑efficient results (compact, rating‑sorted, capped).
- Runs locally via stdio or hosted via Streamable HTTP + OAuth.
- Supports multi‑workspace keys with CUTPRO_WORKSPACE_ID.
- Scalable self‑hosted mode with Redis-backed OAuth.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name CutPro MCP
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install via npx -y @cutpro/mcp and set the CUTPRO_API_KEY environment variable (required for stdio mode). Configure the server in any MCP-compatible client (Claude Code, Cursor, VS Code, Windsurf, Cline, Zed, Gemini CLI, Codex). For hosted access, connect to https://mcp.cut.pro and authorize with OAuth.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

McpServers

{
    "cutpro": {
        "command": "npx",
        "args": [
            "-y",
            "@cutpro/mcp"
        ],
        "env": {
            "CUTPRO_API_KEY": "<YOUR_API_KEY>"
        }
    }
}
## CutPro MCP [![npm version](https://img.shields.io/npm/v/@cutpro/mcp?style=flat-square&color=7C3AED)](https://www.npmjs.com/package/@cutpro/mcp) [![MCP Registry](https://img.shields.io/badge/MCP_Registry-io.github.getcutpro%2Fcutpro-7C3AED?style=flat-square)](https://registry.modelcontextprotocol.io) [![smithery badge](https://smithery.ai/badge/contact-8lma/cutpro)](https://smithery.ai/servers/contact-8lma/cutpro) A Model Context Protocol (MCP) server that turns long videos into viral clips with AI. It exposes the full [CutPro API](https://cut.pro/docs/api-reference) 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](https://cut.pro/studio/me/api-keys). - An MCP-compatible client. ### Standard config Most clients use the same JSON. Add your API key under `env`: ```json { "mcpServers": { "cutpro": { "command": "npx", "args": ["-y", "@cutpro/mcp"], "env": { "CUTPRO_API_KEY": "<your-api-key>" } } } } ``` ### Install [<img src="https://img.shields.io/badge/VS_Code-Install_Server-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white" alt="Install in VS Code">](https://insiders.vscode.dev/redirect?url=vscode%3Amcp%2Finstall%3F%257B%2522name%2522%253A%2522cutpro%2522%252C%2522command%2522%253A%2522npx%2522%252C%2522args%2522%253A%255B%2522-y%2522%252C%2522%2540cutpro%252Fmcp%2522%255D%257D) [<img src="https://img.shields.io/badge/Cursor-Install_Server-000000?style=flat-square&logo=cursor&logoColor=white" alt="Install in Cursor">](https://cursor.com/en/install-mcp?name=cutpro&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBjdXRwcm8vbWNwIl19) [<img src="https://img.shields.io/badge/LM_Studio-Install_Server-4A26C9?style=flat-square" alt="Install in LM Studio">](https://lmstudio.ai/install-mcp?name=cutpro&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBjdXRwcm8vbWNwIl19) [<img src="https://img.shields.io/badge/Goose-Install_Server-1A1A1A?style=flat-square" alt="Install in Goose">](goose://extension?cmd=npx&arg=-y&arg=%40cutpro%2Fmcp&id=cutpro&name=CutPro&description=AI%20video%20clipping%20via%20the%20CutPro%20API) After installing via a button, add your `CUTPRO_API_KEY` to the server's `env`. <details> <summary>Claude Code</summary> ```bash claude mcp add cutpro --env CUTPRO_API_KEY=<your-api-key> -- npx -y @cutpro/mcp ``` </details> <details> <summary>Claude Desktop</summary> Add to `claude_desktop_config.json` (Settings, Developer, Edit Config): ```json { "mcpServers": { "cutpro": { "command": "npx", "args": ["-y", "@cutpro/mcp"], "env": { "CUTPRO_API_KEY": "<your-api-key>" } } } } ``` </details> <details> <summary>Cursor / Windsurf / VS Code (manual)</summary> Add the standard config above to the client's MCP settings (`mcp.json` / `mcpServers`). </details> <details> <summary>Cline</summary> Open the MCP Servers panel, choose Configure, and add the standard config above. </details> <details> <summary>Gemini CLI</summary> ```bash gemini mcp add cutpro npx -y @cutpro/mcp -e CUTPRO_API_KEY=<your-api-key> ``` </details> <details> <summary>Codex</summary> Add to `~/.codex/config.toml`: ```toml [mcp_servers.cutpro] command = "npx" args = ["-y", "@cutpro/mcp"] env = { "CUTPRO_API_KEY" = "<your-api-key>" } ``` </details> <details> <summary>ChatGPT and Claude.ai (hosted, no install)</summary> 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. </details> ## 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 | <details> <summary>Self-hosting the remote (Streamable HTTP + OAuth)</summary> | 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. | ```bash 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). </details> ## Tools <details> <summary>Workspace and balance</summary> - **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. </details> <details> <summary>Videos and uploads</summary> - **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. </details> <details> <summary>Clipping</summary> - **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. </details> <details> <summary>Clips and templates</summary> - **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. </details> <details> <summary>Renders</summary> - **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. </details> <details> <summary>Posts and connections</summary> - **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. </details> Each tool carries read-only / write / destructive annotations so clients can plan calls. ## Links - Docs: [cut.pro/docs/api-reference/mcp](https://cut.pro/docs/api-reference/mcp) - npm: [@cutpro/mcp](https://www.npmjs.com/package/@cutpro/mcp) - MCP Registry: `io.github.getcutpro/cutpro` ## License MIT
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