AI clips from long videos: analyze, clip, render and publish via the CutPro API.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-getcutpro-cutpro": {
"command": "<see-readme>",
"args": []
}
}
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AI clips from long videos: analyze, clip, render and publish via the CutPro API.
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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.
list_clips is rating sorted, capped, and omits long signed URLs unless asked.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>" }
}
}
}
After installing via a button, add your CUTPRO_API_KEY to the server's env.
claude mcp add cutpro --env CUTPRO_API_KEY=<your-api-key> -- npx -y @cutpro/mcp
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>" }
}
}
}
Add the standard config above to the client's MCP settings (mcp.json / mcpServers).
Open the MCP Servers panel, choose Configure, and add the standard config above.
gemini mcp add cutpro npx -y @cutpro/mcp -e CUTPRO_API_KEY=<your-api-key>
Add to ~/.codex/config.toml:
[mcp_servers.cutpro]
command = "npx"
args = ["-y", "@cutpro/mcp"]
env = { "CUTPRO_API_KEY" =
... [View full README on GitHub](https://github.com/getcutpro/mcp#readme)