# Processing

> Use this tool when you need to generate and execute Processing sketches using Java code through a command-line interface, solving problems in creative coding workflows, generative art creation, and interactive visualization development. It takes Java Processing code as input and outputs executable sketches, saving them to a configurable location and launching them as separate windows. This tool is ideal for use cases requiring automated Processing sketch execution, such as data visualization, animation, and game development.

Canonical page: https://skillsregistry.net/skills/twelve2five-processing  
JSON: https://api.skillsregistry.net/v1/skills/twelve2five-processing

## Description

This MCP server enables AI assistants to generate and execute Processing sketches by providing tools to run Java Processing code through the command-line interface. Built using FastMCP, it automatically creates sketch folders with timestamped names, saves .pde files to a configurable location (defaulting to ~/Documents/Processing/sketches), and launches Processing sketches as separate windows without blocking execution. The implementation supports environment variable configuration for custom Processing executable paths and save locations, includes example sketches ranging from simple animations to interactive games, and handles error cases like missing Processing installations, making it valuable for creative coding workflows, generative art creation, and interactive visualization development.

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/twelve2five-processing)
- **Repository:** <https://github.com/twelve2five/processing-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "twelve2five-processing"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/twelve2five-processing` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/twelve2five-processing/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt