AI Code Toolkit

Scale your AI coding agents with scaffolding, architecture patterns, and validation rules

A collection of Model Context Protocol (MCP) servers and tools that help AI coding agents maintain consistency, follow conventions, and scale with your codebase.

Contents

• Why This Exists

• Core Pillars

• Getting Started

  • Prerequisites

  • Quick Start

• Packages

• Our Approach

• Development

• Documentation

• Version Support

• Contributing

• License

Why This Exists

As projects evolve from MVP to production, they develop patterns, conventions, and opinionated approaches. Custom instructions alone struggle to ensure AI agents follow these requirements—especially as complexity grows and context windows fill up.

AI Code Toolkit provides building blocks to scale coding agent capabilities:

• ✅ Generate code that follows your team's conventions

• ✅ Enforce architectural patterns automatically

• ✅ Validate agent outputs programmatically

• ✅ Work with any AI coding agent (Claude, Cursor, etc.)

• ✅ Support any tech stack (Next.js, React, or custom frameworks)

Whether you're bootstrapping a new project or managing a complex monorepo, these tools ensure AI agents integrate seamlessly with your development workflow.

Core Pillars

1. 🏗️ Scaffolding Templates

Combine templating with LLMs to generate standardized code that follows your internal conventions while reducing maintenance overhead.

2. 🎨 Architecture + Design Patterns

Convention over configuration scales. Like Ruby on Rails or Angular, opinionated approaches make code predictable—for both humans and AI agents.

3. ✅ Rules

Pre-flight guidance + post-flight validation = consistent output. Rules provide programmatic checks (quantitative or qualitative) to enforce your processes.

Getting Started

Prerequisites

• Node.js: >= 18 (LTS recommended)

• Package Manager: pnpm (or npm/yarn)

• Git: >= 2.13.2

Quick Start

Option 1: Use as MCP Server (with Claude Desktop)

1. Install the package:

   pnpm install @agiflowai/scaffold-mcp

2. Configure Claude Desktop: Add to your MCP settings:

   { "mcpServers": { "scaffold": { "command": "scaffold-mcp", "args": ["mcp-serve"] } } }

3. Start using it: The MCP server tools will be available in Claude Desktop.

Option 2: Use as CLI

For detailed usage, see the scaffold-mcp documentation.

Packages

@agiflowai/scaffold-mcp

MCP server for scaffolding applications with boilerplate templates and feature generators.

Key Features:

• 🚀 Create projects from boilerplate templates

• 🎯 Add features to existing projects (pages, components, services)

• 📦 Template management (initialize, add from repositories)

• 🔧 Built-in templates: Next.js 15, Vite + React

• 🌐 Multiple transport modes: stdio, HTTP, SSE

• 💻 Standalone CLI mode

View full documentation →

@agiflowai/scaffold-generator

Core utilities and types for scaffold generators. Internal library used by scaffold-mcp.

View source →

Our Approach

🤖 Agent Agnostic

Works with any AI coding agent (Claude Code, Cursor, Windsurf, etc.). Each library provides:

• MCP tools for integration with MCP-compatible agents

• CLI commands for scripting deterministic workflows

🛠️ Tech Stack Agnostic

Built-in templates for popular frameworks:

• Next.js 15

• Vite + React

• More coming soon

Don't see your stack? Use the built-in MCP tools to generate custom templates—the system is fully extensible.

🎯 Coding Tool Specific

Maximize effectiveness by combining three layers:

1. MCP Servers → Let tools guide the agent with their default prompts

2. Custom Instructions → Use CLAUDE.md, AGENTS.md to specify when to use MCP tools

3. Hooks → Intercept tool calls to enforce workflows (e.g., require scaffolding for new files)

Experiment with these layers to find the right balance for your project. There's no one-size-fits-all solution.

Development

This is an Nx monorepo using pnpm for package management.

Common Commands

Code Quality

We use Biome for lightning-fast linting and formatting:

• ⚡ 10-100x faster than ESLint (written in Rust)

• 🎯 All-in-one: Replaces ESLint + Prettier

• 🔧 Zero config: Sensible defaults out of the box

Configuration: biome.json

Publishing

See PUBLISHING.md for the complete release workflow:

Documentation

• Scaffold MCP Guide - Complete guide to the scaffolding MCP server

• Contributing Guide - How to contribute to this project

• Publishing Guide - Release and versioning workflow

Version Support

Security patches are applied to non-EOL versions. Features are added to the latest version only.

Contributing

We welcome contributions! Whether it's bug reports, feature requests, or pull requests—all contributions are appreciated.

How to contribute:

1. 🍴 Fork the repository

2. 🌿 Create a feature branch (git checkout -b feature/amazing-feature)

3. 💻 Make your changes

4. ✅ Run tests and linting (pnpm test && pnpm lint)

5. 📝 Commit your changes (follow conventional commits)

6. 🚀 Push to your branch (git push origin feature/amazing-feature)

7. 🎉 Open a Pull Request

See CONTRIBUTING.md for detailed guidelines.

License

AGPL-3.0 © AgiflowIO

Built with ❤️ by the AgiflowIO team

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