developer-tools

Scaffold Generator

by agiflow

Quickly rp prototype web apps with Scaffold Generator: create consistent scaffolding using templates, variable substitut

Generates code scaffolding for modern web applications using template-based boilerplate creation and feature addition with variable substitution, conditional file inclusion, and schema validation for rapid prototyping and consistent development patterns.

github stars

146

Template-based with variable substitutionBuilt-in schema validationWorks with Claude, Cursor, Gemini CLI

best for

  • / Frontend developers starting new projects
  • / Teams enforcing consistent code structure
  • / Rapid prototyping and MVP development
  • / Standardizing development workflows

capabilities

  • / Generate project scaffolds from templates
  • / Add features to existing codebases
  • / Substitute variables in template files
  • / Validate code structure against schemas
  • / Create consistent development patterns
  • / Configure MCP server setups automatically

what it does

Generates code scaffolding and boilerplate for modern web applications using customizable templates with variable substitution and schema validation.

about

Scaffold Generator is a community-built MCP server published by agiflow that provides AI assistants with tools and capabilities via the Model Context Protocol. Quickly rp prototype web apps with Scaffold Generator: create consistent scaffolding using templates, variable substitut It is categorized under developer tools.

how to install

You can install Scaffold Generator in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

AGPL-3.0

Scaffold Generator is released under the AGPL-3.0 license.

readme

AI Code Toolkit

npm version License: AGPL-3.0 Discord

This repo provides:

  • project and feature scaffolding via templates
  • file-level design guidance before edits
  • rule-based review after edits
  • design-system discovery for frontend work

Quick Start

Requirements:

  • Node.js >= 18
  • an MCP-compatible agent such as Claude Code, Cursor, or Gemini CLI

1. Initialize a Workspace

# Existing project
npx @agiflowai/aicode-toolkit init

# New project
npx @agiflowai/aicode-toolkit init --name my-app --project-type monolith

This creates templates/ and .toolkit/settings.yaml. Projects reference templates through sourceTemplate in project.json or .toolkit/settings.yaml.

2. Configure MCP

init can configure MCP automatically. For manual setup, add the servers you need to your agent config.

Example for Claude Code:

{
  "mcpServers": {
    "scaffold-mcp": {
      "command": "npx",
      "args": ["-y", "@agiflowai/scaffold-mcp", "mcp-serve", "--admin-enable"]
    },
    "architect-mcp": {
      "command": "npx",
      "args": [
        "-y", "@agiflowai/architect-mcp", "mcp-serve",
        "--admin-enable",
        "--design-pattern-tool", "codex",
        "--review-tool", "gemini-cli"
      ]
    },
    "style-system": {
      "command": "npx",
      "args": ["-y", "@agiflowai/style-system", "mcp-serve"]
    }
  }
}

Useful flags:

  • --admin-enable: enable admin/template-authoring tools
  • --design-pattern-tool <tool>: use an LLM to filter design patterns
  • --review-tool <tool>: use an LLM for review output

3. Verify

Ask the agent:

What boilerplates are available?

It should call list-boilerplates. If not, restart the agent.

Repo Layout

AI agent
  ├─ scaffold-mcp
  ├─ architect-mcp
  ├─ style-system
  └─ one-mcp
        ↓
     templates/
       ├─ scaffold.yaml
       ├─ architect.yaml
       └─ RULES.yaml

scaffold-mcp

Generates projects and feature boilerplate from templates.

Core tools:

  • list-boilerplates
  • use-boilerplate
  • list-scaffolding-methods
  • use-scaffold-method

Admin tools:

  • generate-boilerplate
  • generate-feature-scaffold
  • generate-boilerplate-file

architect-mcp

Provides file-specific patterns before edits and reviews changes against RULES.yaml.

Core tools:

  • get-file-design-pattern
  • review-code-change

Admin tools:

  • add-design-pattern
  • add-rule

style-system

Provides theme, CSS class, and component discovery tools.

Core tools:

  • list_themes
  • get_css_classes
  • get_component_visual
  • list_shared_components
  • list_app_components

one-mcp

Provides progressive tool discovery to reduce MCP prompt overhead.

Typical Workflow

Create a Project

User: "Create a Next.js app called dashboard"

Agent:
1. list-boilerplates
2. use-boilerplate
3. Project is generated

Add a Feature

User: "Add a products API route"

Agent:
1. list-scaffolding-methods
2. use-scaffold-method
3. Feature files are generated

Edit a File Safely

User: "Add a products page"

Agent:
1. get-file-design-pattern
2. edit the file using the returned patterns and rules
3. review-code-change
4. fix any violations

Style a Component

User: "Style the button with our theme colors"

Agent:
1. get_css_classes
2. list_shared_components
3. update the component
4. get_component_visual

Template Structure

templates/
└── nextjs-15/
    ├── scaffold.yaml
    ├── architect.yaml
    ├── RULES.yaml
    └── boilerplate/

scaffold.yaml

Defines boilerplates and feature scaffolds.

boilerplates:
  - name: nextjs-15-app
    description: "Next.js 15 with App Router"
    targetFolder: apps
    includes:
      - boilerplate/**/*

features:
  - name: add-route
    description: "Add route with page and layout"
    variables_schema:
      name: { type: string, required: true }
    includes:
      - features/route/**/*

architect.yaml

Defines file-level patterns that should be shown before edits.

patterns:
  - name: server-component
    description: "Default for page components"
    file_patterns:
      - "**/app/**/page.tsx"
    description: |
      - Use async/await for data fetching
      - Keep components focused on rendering
      - Move business logic to server actions

RULES.yaml

Defines review rules. Rules can be inherited from a global templates/RULES.yaml.

version: '1.0'
template: typescript-lib
rules:
  - pattern: src/services/**/*.ts
    description: Service Layer Implementation Standards
    must_do:
      - rule: Create class-based services with single responsibility
        codeExample: |-
          export class DataProcessorService {
            async processData(input: string): Promise<ProcessedData> {
              // Implementation
            }
          }
      - rule: Use dependency injection for composability
    must_not_do:
      - rule: Create static-only utility classes - use functions
        codeExample: |-
          // ❌ BAD
          export class Utils {
            static format(s: string) {}
          }

          //  GOOD
          export function format(s: string): string {}

Project Types

Monorepo

Each project references its template in project.json.

my-workspace/
├── apps/
│   └── web-app/
│       └── project.json
├── packages/
│   └── shared-lib/
│       └── project.json
└── templates/

Monolith

Monoliths use .toolkit/settings.yaml.

version: "1.0"
projectType: monolith
sourceTemplate: nextjs-15

Built-in Templates

Included templates:

TemplateStackIncludes
nextjs-drizzleNext.js 15, App RouterTypeScript, Tailwind 4, Drizzle, Storybook
typescript-libTypeScript LibraryESM/CJS, Vitest, TSDoc
typescript-mcp-packageMCP ServerCommander, MCP SDK

Custom Templates

For template authoring, start from an existing repo or template and use the admin prompts:

/generate-boilerplate
/generate-feature-scaffold

For design/rule authoring, use:

  • add-design-pattern
  • add-rule

Supported Agents

AgentConfig LocationStatus
Claude Code.mcp.jsonSupported
Cursor.cursor/mcp.jsonSupported
Gemini CLI.gemini/settings.jsonSupported
Codex CLI.codex/config.jsonSupported
GitHub CopilotVS Code settingsSupported
Windsurf-Planned

Packages

PackageDescription
@agiflowai/aicode-toolkitCLI for init and config sync
@agiflowai/scaffold-mcpScaffolding server
@agiflowai/architect-mcpPattern and review server
@agiflowai/style-systemDesign-system server
@agiflowai/one-mcpMCP proxy for progressive discovery

Contributing

See CONTRIBUTING.md.

License

AGPL-3.0


Issues · Discord · Website

FAQ

What is the Scaffold Generator MCP server?
Scaffold Generator is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Scaffold Generator?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Scaffold Generator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Scaffold Generator against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Scaffold Generator is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Scaffold Generator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Scaffold Generator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Scaffold Generator surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Scaffold Generator has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Scaffold Generator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Scaffold Generator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Scaffold Generator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.