text2d

text2d

Enables AI assistants to procedurally generate, edit, quantize, and export 2D retro pixel art textures and tilesets for game development, with built-in palettes, dithering, and pixel-level manipulation tools.

Category
Visit Server

README

text2d — 2D Retro Pixel Art Texture MCP Server

A high-performance Model Context Protocol (MCP) server that empowers AI assistants to procedurally generate, manipulate, and export 2D retro pixel art textures and tilesets for game development.


Features

  • Image to Retro Pixel Art Conversion: Ingest external PNG files and automatically downscale, quantize to retro palettes, and apply Bayer dithering via pixelize_image.
  • Procedural Texture Synthesis: Deterministic generation of wood, stone (cobblestone/rock), brick, grass, metal (brushed plates with rivets), and water caustics.
  • Pixel-Level Primitives: Full control via set_pixel, set_pixel_batch, draw_shape (lines, rects, circles), and flood_fill.
  • Retro Palettes & Quantization: Built-in authentic color palettes including PICO-8, DawnBringer 32 (DB32), Endesga 32, GameBoy, NES Classic, and Cyberpunk Neon.
  • Pixel-Art Post-Processing: Bayer ordered dithering (2x2, 4x4, 8x8) and 1px inner/outer pixel-perfect outlines.
  • Export Options: PNG files with nearest-neighbor integer scaling, Base64 Data URIs, ASCII Unicode block previews, and 2D JSON color grids.

Visual Examples & Gallery

1. Image Pixelization (pixelize_image)

Convert high-resolution realistic photos or assets into authentic retro pixel art with automatic palette quantization and Bayer dithering.

Original Input Endesga 32 (32x32) PICO-8 (32x32) GameBoy (32x32)
<img src="examples/input/realistic_car.jpg" width="160" alt="Original Photo" /> <img src="examples/output/car_pixel_32_endesga.png" width="160" alt="Endesga 32" /> <img src="examples/output/car_pixel_32_pico8.png" width="160" alt="PICO-8" /> <img src="examples/output/car_pixel_32_gameboy.png" width="160" alt="GameBoy" />
DawnBringer 32 (48x48) Cyberpunk Neon (64x64)
<img src="examples/output/car_pixel_48_db32.png" width="200" alt="DB32 48x48" /> <img src="examples/output/car_pixel_64_cyberpunk.png" width="200" alt="Cyberpunk 64x64" />

2. Procedural Texture Synthesis (generate_texture)

Generate seamless, deterministic retro textures in seconds without external assets.

Wood (wood) Stone (stone) Brick (brick)
<img src="examples/output/wood.png" width="150" alt="Wood Texture" /> <img src="examples/output/stone.png" width="150" alt="Stone Texture" /> <img src="examples/output/brick.png" width="150" alt="Brick Texture" />
Grass (grass) Metal (metal) Water (water)
<img src="examples/output/grass.png" width="150" alt="Grass Texture" /> <img src="examples/output/metal.png" width="150" alt="Metal Texture" /> <img src="examples/output/water.png" width="150" alt="Water Texture" />

MCP Tools Matrix

Tool Name Description Key Parameters
pixelize_image Ingests external PNG and converts to 2D retro pixel art file_path, target_width, target_height, palette, sampling, dither, export_output_path
create_canvas Initializes a new in-memory pixel canvas width, height, palette, mode, backgroundColor
generate_texture Synthesizes a procedural retro texture canvas_id, texture_type, seed, palette, options
set_pixel Sets a single pixel at (x, y) canvas_id, x, y, color
set_pixel_batch Batch updates multiple coordinates canvas_id, pixels: [{x, y, color}]
draw_shape Draws rasterized line, rect, or circle canvas_id, shape, x1, y1, x2, y2, color, filled
flood_fill Contiguous area flood fill canvas_id, x, y, color
apply_dither Applies Bayer ordered dithering canvas_id, matrix_size, spread
apply_outline Draws 1px pixel-perfect outline canvas_id, color, mode
export_texture Exports canvas to PNG, Data URI, ASCII or JSON canvas_id, format, file_path, scale
list_palettes Lists all built-in retro palettes None
list_canvases Lists active canvases in memory None
get_canvas_info Inspects canvas metadata and dimensions canvas_id
delete_canvas Frees canvas from memory canvas_id

Installation & Usage

You can install and run text2d directly from GitHub without publishing to npm:

1. Global Installation (Recommended)

Install globally directly from the GitHub repository:

npm install -g github:al3duc/text2d-mcp

Once installed, the text2d command is available system-wide.


MCP Client Configuration

Add text2d to your MCP client configuration (e.g. claude_desktop_config.json, mcp_config.json, or Cursor):

Option A: Using Global Installation (Simplest)

{
  "mcpServers": {
    "text2d": {
      "command": "text2d"
    }
  }
}

Option B: Direct Execution via npx (No permanent install)

{
  "mcpServers": {
    "text2d": {
      "command": "npx",
      "args": [
        "-y",
        "github:al3duc/text2d-mcp"
      ]
    }
  }
}

Option C: Claude Code CLI Command

If using Claude Code, register it with a single terminal command:

claude mcp add text2d -- npx -y github:al3duc/text2d-mcp

Option D: Local Clone (Development)

git clone https://github.com/al3duc/text2d-mcp.git
cd text2d-mcp
npm install
npm run build
{
  "mcpServers": {
    "text2d": {
      "command": "node",
      "args": [
        "<PATH_TO_TEXT2D_REPOSITORY>/dist/index.js"
      ]
    }
  }
}

Note: Replace <PATH_TO_TEXT2D_REPOSITORY> with the absolute path to your cloned repository.


Build & Test

# Install dependencies
npm install

# Run unit & integration tests
npm test

# Build TypeScript to dist/
npm run build

# Generate procedural texture samples (wood, stone, brick, grass, metal, water)
npx tsx examples/generate_samples.ts

# Test converting realistic images from examples/input/ to pixel art
npx tsx examples/test_car_pixelize.ts

License

This project is licensed under the MIT License - see the LICENSE file for details.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured