Deploy Flask apps directly from your AI assistant using Model Context Protocol. Zero config. AI-managed environments. Instant rollback.
Your AI detects Flask automatically and configures the build pipeline. No config files to write.
Set environment variables with natural language. The AI handles secrets, database URLs, and API keys.
Something wrong? Tell your AI to roll back. Previous versions are always one sentence away.
The AI detects Flask, identifies the app factory or module, and configures gunicorn.
Deploy my Flask app from github.com/me/my-flask-app
Configure production settings, database connections, and secrets through natural language.
Set FLASK_ENV=production and configure DATABASE_URL
CreateOS deploys Flask with gunicorn, handling process management and health checks.
Deploy with gunicorn and 2 workers
View real-time logs, monitor performance, and scale your Flask app from chat.
Show logs and scale to handle more traffic
Your AI auto-configures these environment variables for Flask:
DATABASE_URLSECRET_KEYFLASK_ENVREDIS_URLFor Flask apps, we recommend PostgreSQL. Provision it with one sentence:
> Create a PostgreSQL database and inject the connection string into my Flask app
Deploy Flask with MCP from any of these AI tools:
Add the CreateOS MCP endpoint to your AI tool and deploy Flask in seconds:
{
"mcpServers": {
"createos": {
"url": "https://api-createos.nodeops.network/mcp",
"headers": { "X-Api-Key": "YOUR_KEY" }
}
}
}제품 업데이트, 빌더 스토리, 더 빠르게 출시할 수 있는 기능에 대한 얼리 액세스를 받아보세요.
CreateOS는 아이디어가 컨셉에서 라이브 배포까지 원활하게 이동하는 통합 지능형 워크스페이스입니다. 도구, 인프라, 워크플로 간의 컨텍스트 전환을 제거하고 CreateOS 마켓플레이스에서 즉시 아이디어를 수익화할 수 있습니다.