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AI Code Toolkit

by AgiFlow
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AGPL 3.0
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AI Code Toolkit

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

npm version License: AGPL-3.0 Node.js Version

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

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

# Install globally or use npx pnpm install -g @agiflowai/scaffold-mcp # Initialize templates (auto-downloads official templates) scaffold-mcp init # List available boilerplates scaffold-mcp boilerplate list # Create a new project scaffold-mcp boilerplate create scaffold-nextjs-app \ --vars '{"appName":"my-app","withDrizzle":true}' # Add features to existing projects scaffold-mcp scaffold list ./apps/my-app scaffold-mcp scaffold add scaffold-route \ --project ./apps/my-app \ --vars '{"routePath":"about","pageTitle":"About Us"}'

Key Features:

  • 🎁 Auto-download templates: init command downloads official templates from GitHub

  • 🔗 GitHub subdirectory support: Add templates from specific folders in repositories

  • 🌐 Multiple transport modes: stdio (MCP), HTTP, SSE, or standalone CLI

  • 📦 Built-in templates: Next.js 15 with Drizzle ORM, Storybook, and more

For detailed usage, see the scaffold-mcp documentation.

Template Management

The init command automatically downloads official templates from the AgiFlow repository:

# Initialize and auto-download official templates scaffold-mcp init # Skip auto-download scaffold-mcp init --no-download # Custom templates path scaffold-mcp init --path ./custom-templates

Add additional templates from GitHub (supports subdirectories):

# Add from full repository scaffold-mcp add --name my-template --url https://github.com/user/repo # Add from repository subdirectory scaffold-mcp add \ --name nextjs-template \ --url https://github.com/user/repo/tree/main/templates/nextjs

Current Templates:

  • nextjs-15-drizzle: Next.js 15 + App Router + TypeScript + Tailwind CSS 4 + Storybook + Optional Drizzle ORM

    • Boilerplate: Full application setup

    • Features: Routes, components, API routes, auth, services, and more

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

  • 🎙️ Slash command prompts for AI coding agents

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.

Slash Command Prompts

The scaffold-mcp server provides built-in slash commands for AI coding agents like Claude Code:

For Users:

  • /scaffold-mcp:scaffold-application - Guide the agent to create a new application from boilerplate templates

  • /scaffold-mcp:scaffold-feature - Guide the agent to add features (pages, components, services) to existing projects

For Template Creators:

  • /scaffold-mcp:generate-boilerplate - Guide the agent to create a new boilerplate template configuration

  • /scaffold-mcp:generate-feature-scaffold - Guide the agent to create a new feature scaffold configuration

These prompts provide step-by-step instructions to the AI agent, ensuring it follows the correct workflow for scaffolding tasks. They're automatically available when the MCP server is configured in your coding agent.

📖 Learn how to use prompts →

Development

This is an Nx monorepo using pnpm for package management.

Common Commands

# Install dependencies pnpm install # Build all packages pnpm build # Build a specific package pnpm exec nx build scaffold-mcp # Run tests pnpm test pnpm exec nx test scaffold-mcp # Lint and format pnpm lint # Check for issues pnpm lint:fix # Auto-fix issues pnpm format # Format code pnpm format:check # Check formatting # Type checking pnpm typecheck pnpm exec nx typecheck scaffold-mcp # Visualize project graph pnpm exec nx graph

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:

# Preview release (dry run) pnpm release:dry-run # Publish to npm pnpm release

Documentation

Version Support

Component

Requirement

Node.js

>= 18

(LTS recommended)

Git

>= 2.13.2

pnpm

>= 9

(or use npm/yarn)

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

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.

  1. Contents
    1. Why This Exists
      1. Core Pillars
        1. 1. 🏗️ Scaffolding Templates
        2. 2. 🎨 Architecture + Design Patterns
        3. 3. ✅ Rules
      2. Getting Started
        1. Prerequisites
        2. Quick Start
        3. Template Management
      3. Packages
        1. @agiflowai/scaffold-mcp
        2. @agiflowai/scaffold-generator
      4. Our Approach
        1. 🤖 Agent Agnostic
        2. 🛠️ Tech Stack Agnostic
        3. 🎯 Coding Tool Specific
      5. Development
        1. Common Commands
        2. Code Quality
        3. Publishing
      6. Documentation
        1. Version Support
          1. Contributing
            1. License

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