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Kalypsokichu-code

QR Code Generator MCP

by Kalypsokichu-code
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

QR Code Generator + MCP

A standalone QR code generator with beautiful styling options and Model Context Protocol (MCP) integration.

Features

Web App

  • 10 pre-designed style presets

  • Mobile-responsive design

  • Custom logo upload support

  • Export as SVG or PNG

  • Logo positioning options (center, bottom-right)

  • Dark/Light/System theme switcher

  • Interactive sound effects with toggle control

  • Built with Next.js 15 and React 19

  • Full Kalypso design system styling

MCP Integration

  • AI-powered QR code generation via Claude Desktop & Cursor

  • HTTP and stdio transport support

  • Access all 10 style presets programmatically

  • No browser needed - generate QR codes directly from AI tools

  • Hosted endpoint or local deployment options

Related MCP server: qr-maker

Getting Started

Web App

Installation

npm install

Development

npm run dev

Open http://localhost:3000 to see the QR code generator.

Build

npm run build:next
npm start

MCP Server

Quick Start with Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "qr-tool": {
      "url": "https://qr-tool-mcp.vercel.app/api/mcp"
    }
  }
}

Restart Claude Desktop and you can now generate QR codes with AI!

Example usage:

Generate a QR code for https://instagram.com/kalypsodesigns using the neon-pulse style

Local MCP Server Development

npm run build:mcp
npm run start:mcp

For detailed setup instructions:

Project Structure

├── src/
│   ├── app/                    # Next.js app directory
│   │   ├── qr-generator/       # QR code generator feature
│   │   ├── layout.tsx          # Root layout
│   │   └── page.tsx            # Home page
│   ├── components/             # Reusable components
│   │   ├── ui/                 # UI components (button, input, etc.)
│   │   └── mobile-tool-wrapper.tsx
│   ├── hooks/                  # Custom React hooks
│   ├── lib/                    # Utility functions
│   └── styles/                 # Global styles
├── public/                     # Static assets
└── package.json

Available Scripts

Web App

  • npm run dev - Start development server

  • npm run build:next - Build Next.js app for production

  • npm start - Start production server

MCP Server

  • npm run build:mcp - Build MCP server

  • npm run start:mcp - Start MCP server (stdio mode)

  • npm run build - Build both web app and MCP server

Code Quality

  • npm run lint - Run linter

  • npm run lint:fix - Fix linting issues

  • npm run format - Format code with Biome

  • npm run type-check - Run TypeScript type checking

Technologies

Frontend

  • Next.js 15 - React framework

  • React 19 - UI library

  • TypeScript - Type safety

  • Tailwind CSS - Styling

  • Radix UI - Accessible components

  • next-themes - Theme management

  • Motion - Smooth animations

MCP Server

  • @modelcontextprotocol/sdk - MCP protocol implementation

  • Zod - Schema validation

  • jsdom - Headless DOM for server-side QR generation

  • qr-code-styling - QR code generation

  • jszip - ZIP file generation for batch downloads

Code Quality

  • Biome - Linting and formatting

  • Husky - Git hooks

  • TypeScript - Type safety

MCP Tools

generate_qr_code

Generate a styled QR code with custom options.

Parameters:

  • url (required) - The URL or text to encode

  • style (optional) - Style preset ID (default: "slate-ember")

  • format (optional) - "svg" or "png" (default: "svg")

  • size (optional) - Dimensions 256-2048px (default: 768)

  • logoPosition (optional) - "center" or "bottom-right"

generate_qr_urls_batch

Generate QR codes for multiple URLs at once. Returns a single ZIP file download URL containing all QR codes with filenames based on the URLs.

Parameters:

  • urls (required) - Array of URLs or text content to encode (max 100)

  • style (optional) - Style preset to apply to all QR codes (default: "slate-ember")

Returns: A single download URL that delivers a ZIP file containing all QR codes as SVG files. Filenames are automatically generated from the URLs (e.g., 001-example-com-page.svg, 002-github-com-user.svg).

Example:

Generate QR codes for these URLs: https://example.com, https://github.com/user, https://twitter.com/handle

get_available_styles

List all available QR code style presets with color schemes.

preview_qr_url

Generate a shareable web preview URL for customization.

Available Styles

  1. slate-ember - Dark slate with orange accent (default)

  2. ink-lime - Deep black with lime green

  3. charcoal-cyan - Navy charcoal with cyan

  4. night-sky - Midnight blue with sky blue

  5. graphite-gold - Dark graphite with gold

  6. espresso-rose - Dark brown with rose pink

  7. plum-ice - Deep purple with lavender

  8. forest-mint - Forest green with mint

  9. cocoa-orange - Warm brown with orange

  10. mono-high - High contrast black & white

License

MIT License - see LICENSE file for details.

Available Tools

4 tools
generate_qr_codeC

Generate a QR code with custom styling. Returns base64-encoded SVG image data that can be saved or displayed. Supports multiple visual styles.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL or text content to encode in the QR code
styleNoVisual style preset for the QR code. Default: slate-ember
sizeNoQR code dimensions in pixels. Default: 768. Range: 256-2048

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool 'Returns base64-encoded SVG image data that can be saved or displayed,' which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether the operation is idempotent—critical for a generation tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with two sentences that efficiently convey the core functionality and output. Every sentence adds value: the first defines the action and output, the second notes styling support. No wasted words, though it could be slightly more structured for a perfect 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is partially complete. It covers the output format and styling but lacks details on error cases, performance, or integration with siblings. Without annotations or output schema, more behavioral context would improve completeness for safe agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'custom styling' and 'multiple visual styles,' hinting at the 'style' parameter, but doesn't elaborate on the semantics of styles or other parameters. With high schema coverage, the baseline is 3, as the schema already documents parameters well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate a QR code with custom styling.' It specifies the verb ('Generate') and resource ('QR code'), and mentions the output format ('base64-encoded SVG image data'). However, it doesn't explicitly differentiate from sibling tools like 'generate_qr_urls_batch' (batch processing) or 'preview_qr_url' (preview functionality), which would be needed for a score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'custom styling' and 'multiple visual styles,' but doesn't compare to siblings like 'generate_qr_urls_batch' for bulk operations or 'preview_qr_url' for testing. There's no explicit when/when-not usage context, leaving the agent to infer based on tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

generate_qr_urls_batchA

Generate QR code download URLs for multiple URLs at once. Perfect for batch processing CSV files or lists. Returns a single ZIP file download URL containing all QR codes with filenames based on the URLs. Maximum 100 URLs per batch.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlsYesArray of URLs or text content to encode (max 100)
styleNoStyle preset to apply to all QR codes. Default: slate-ember

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool generates download URLs, returns a ZIP file, and has a maximum batch size of 100 URLs. However, it lacks details on permissions, rate limits, error handling, or what happens if URLs are invalid, which are important for a batch processing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by usage context and key constraints, all in three concise sentences with zero waste. Each sentence earns its place by adding value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (batch processing with 2 parameters) and no annotations or output schema, the description is adequate but has gaps. It covers the purpose, output format, and limits, but lacks details on authentication, error responses, or file naming conventions in the ZIP, which could be helpful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Generate QR code download URLs'), resource ('multiple URLs at once'), and distinguishes from siblings by emphasizing batch processing for multiple URLs versus single QR generation. It explicitly mentions the output format (ZIP file) and scope (max 100 URLs).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool ('Perfect for batch processing CSV files or lists'), but does not explicitly mention when not to use it or name alternatives like 'generate_qr_code' for single URLs. It implies usage for bulk operations without detailing exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_available_stylesA

Get a list of all available QR code style presets with their color schemes. Use this to discover styling options before generating QR codes.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It describes the tool as a read operation ('Get a list'), which implies it's non-destructive and likely read-only, but doesn't explicitly state permissions, rate limits, or return format details. The description adds basic behavioral context but lacks depth for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with zero waste: the first states the purpose, and the second provides usage guidelines. It is front-loaded with the core action and efficiently conveys all necessary information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose and usage well, but lacks details on return format or behavioral traits like error handling. For a simple list tool, this is sufficient but not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose and usage. A baseline of 4 is applied as it compensates well for the lack of parameters by providing clear context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get a list') and resource ('all available QR code style presets with their color schemes'), distinguishing it from sibling tools like generate_qr_code which creates codes, generate_qr_urls_batch which batches generation, and preview_qr_url which previews URLs. It explicitly identifies what is being retrieved and why.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use this to discover styling options before generating QR codes.' This provides clear context for usage (pre-generation discovery) and implies an alternative (use other tools for actual generation), guiding the agent effectively.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

preview_qr_urlA

Generate a shareable web preview URL for a QR code. Returns a link to the web interface where users can view, customize, and download the QR code.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL or text to encode
styleNoStyle preset ID. Default: slate-ember

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the tool generates a shareable URL (not the QR image itself) and that the URL leads to a web interface for viewing, customizing, and downloading. However, it omits details like authentication requirements, rate limits, or whether the URL is permanent, which are important for a tool involving web resources.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence and adds useful context in the second. Both sentences earn their place by clarifying the output and its use, with zero wasted words, making it highly efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is mostly complete. It explains what the tool does and the nature of the output (a web interface link), but it could improve by addressing potential behavioral gaps like URL lifespan or error handling. Since there's no output schema, the description adequately covers the return value context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the schema already documents both parameters ('url' and 'style') adequately. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, but it doesn't need to compensate since the schema is comprehensive. Baseline 3 is appropriate here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Generate a shareable web preview URL for a QR code') and the resource ('QR code'), distinguishing it from sibling tools like 'generate_qr_code' (which likely creates the QR image directly) and 'generate_qr_urls_batch' (which handles multiple). The verb 'generate' and target 'web preview URL' are precise.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning the output ('a link to the web interface where users can view, customize, and download the QR code'), suggesting it's for interactive previews rather than direct generation. However, it lacks explicit guidance on when to use this tool versus alternatives like 'generate_qr_code' or 'get_available_styles', leaving the context somewhat inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 4 tool updatesv1.0.0
    • First observedgenerate_qr_code
    • First observedgenerate_qr_urls_batch
    • First observedget_available_styles
    • First observedpreview_qr_url
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TDQS

A3.8/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: generate_qr_code creates a single QR code, generate_qr_urls_batch handles batch processing, get_available_styles lists styling options, and preview_qr_url provides a web preview. The descriptions reinforce these unique roles, making misselection unlikely.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (e.g., generate_qr_code, get_available_styles). The verbs (generate, get, preview) are appropriate and predictable, creating a cohesive naming convention throughout the set.

Tool Count5/5

With 4 tools, this server is well-scoped for a QR code generator, covering key operations like single generation, batch processing, style discovery, and previewing. Each tool earns its place without feeling excessive or insufficient for the domain.

Completeness4/5

The tool set covers the core QR code generation workflow effectively, including creation, batch handling, style options, and previews. A minor gap exists in lacking explicit update or delete operations for generated codes, but this is not critical for the typical use case, and agents can work around it.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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