Introduction

From the Roots to the Fruits. It's connected. It's simply Frootful.

FrootAI is an open ecosystem that unifies the GenAI landscape — binding Infrastructure, Platform, and Application teams with a shared protocol, shared primitives, and shared quality gates. Every piece understands and builds on the others so that Infra, Platform, and App teams build AI — Frootfully.

What Problem Does FrootAI Solve?

The AI tooling ecosystem has produced hundreds of capable building blocks — agents, retrieval pipelines, prompt templates, guardrails, evaluation harnesses, infrastructure modules — but no standard for wiring them together. Each framework (LangChain, Semantic Kernel, AutoGen, CrewAI) defines its own composition model, and each platform (Azure AI Foundry, AWS Bedrock, Vertex AI) adds its own orchestration layer.

Protocols like MCP standardize tool calling. A2A standardizes delegation. AG-UI standardizes rendering. But none address the fundamental question: how do you declare which primitives a system uses, how they share context, and what quality thresholds they must meet?

FrootAI answers that question with the FAI Protocol.

Core Concepts

FAI Protocol

The fai-manifest.json is the Dockerfile equivalent for AI systems — a single declarative file that wires primitives, knowledge, WAF pillars, and guardrails into one coherent manifest:

{
  "play": "01-enterprise-rag",
  "version": "1.0.0",
  "context": {
    "knowledge": ["R2-RAG-Architecture", "O4-Azure-AI-Services"],
    "waf": ["security", "reliability", "cost-optimization"]
  },
  "primitives": {
    "agents": ["./.github/agents/builder.agent.md"],
    "instructions": ["./.github/copilot-instructions.md"],
    "skills": ["./.github/skills/rag-indexer"]
  }
}

Learn more in the FAI Protocol concept page.

Primitives

Six building block types that work standalone and auto-wire when placed inside a solution play:

Type	Format	Purpose
Agents	.agent.md	AI personalities with tools, model preferences, and WAF alignment
Instructions	.instructions.md	Auto-applied coding standards scoped by file glob
Skills	SKILL.md folder	Multi-step procedures the agent can execute
Hooks	hooks.json	Event-driven guardrails triggered by lifecycle events
Plugins	plugin.json	Themed bundles of agents + skills + hooks
Workflows	.yml	Multi-agent orchestration pipelines

Solution Plays

100 pre-built, deployable AI architectures — each shipping with a full DevKit, TuneKit, SpecKit, Bicep infrastructure, and evaluation pipeline. From Enterprise RAG to Edge AI, every play is wired through the FAI Protocol.

Quick Preview

# Start the MCP server — works with Copilot, Claude, Cursor, Windsurf
npx frootai-mcp@latest

# Scaffold a new solution play
npx frootai init-devkit 01

# Validate all primitives
npm run validate:primitives

What Makes FrootAI Different?

Feature	FrootAI	Others
Protocol-level composition	fai-manifest.json wires 9 primitive types	Framework-specific, non-portable
WAF alignment	Every primitive maps to 6 Well-Architected pillars	Ad hoc or missing
100 solution plays	Complete, deployable architectures with IaC	Samples or templates
Quality gates	Guardrails enforced at the protocol level	Manual or per-framework
Multi-channel distribution	npm, PyPI, Docker, VS Code, MCP, CLI	Single-channel

The FROOT Framework

FROOT = Foundations · Reasoning · Orchestration · Operations · Transformation

Layer	What You Learn
F	Tokens, models, glossary, Agentic OS
R	Prompts, RAG, grounding, deterministic AI
O	Semantic Kernel, agents, MCP, tools
O	Azure AI Foundry, GPU infra, Copilot ecosystem
T	Fine-tuning, responsible AI, production patterns

Next Steps

• Quick Start — zero to running in 5 minutes
• Installation — all distribution channels
• Your First Solution Play — build and deploy Play 01
• FAI Protocol — deep-dive into the wiring spec
• Primitives — the 6 building block types