FrootAI CLI
Scaffold projects, search knowledge, estimate costs, and validate configs — all from the terminal. Ships with the MCP Server package. No extra install needed.
No install needed — runs via npx
npx frootai <command>Or if you've installed frootai-mcp globally: just frootai <command>
Commands
frootai initInteractive project scaffolding. 3 questions → complete FrootAI project with .github Agentic OS, DevKit, TuneKit, and MCP config.
frootai scaffold <play>Scaffold a specific solution play (e.g., frootai scaffold 01-enterprise-rag). Creates the full project structure.
frootai search <query>Search the FrootAI knowledge base from terminal. Returns relevant module sections.
frootai cost <play> [scale]Estimate monthly Azure cost for a play. Usage: frootai cost 01 dev or frootai cost 07 prod.
frootai validateValidate your project's FrootAI config files (.github structure, config/*.json, agent.md).
frootai doctorCheck your environment: Node version, MCP server status, VS Code extension, Git config.
frootai deploy <play>Deploy a solution play to Azure. Walks through Bicep deployment with parameter prompts.
frootai helpShow all available commands and usage examples.
Example: frootai init
$ npx frootai init
🌳 FrootAI™ CLI v3.1.2
From the Roots to the Fruits
What are you building?
1) Enterprise RAG
2) AI Agent
3) AI Gateway
4) Content Moderation
5) Multi-modal
6) Custom (pick from 20 plays)
Choose [1-6]: 1
Target scale?
1) dev — Local development
2) prod — Production, HA
Choose [1-2]: 1
Project name [my-ai-project]: my-rag-app
✅ Created my-rag-app/ with:
└── .github/ (Agentic OS — 19 files)
└── .vscode/mcp.json
└── config/ (openai.json, search.json, ...)
└── infra/main.bicep
└── evaluation/
└── agent.md