MagicBall IDE: AI-native information workbench

This page is a plain-text, AI-readable product overview for search engines, AI search systems, and large language models. The concise public homepage remains at https://upservice.cc.

What is MagicBall?

MagicBall is an AI-native information workbench from UpService. It evolved from SCE, the Scene Content Engine, and is designed to help humans and AI agents advance software projects through a governed loop of Spec, DSL, and Audit.

MagicBall is not only an AI coding interface. It is a workbench for making human intent, software-system capability, and long-term software evolution more controllable in AI-assisted project work.

Core loop: Spec, DSL, Audit

• Spec controls communication between humans and AI agents through requirements, design, tasks, acceptance criteria, boundaries, and evidence.
• DSL controls communication between AI agents and software systems by registering stable capabilities, parameters, preconditions, actions, failures, version constraints, and evidence rules.
• Audit controls long-term system evolution by checking function, DSL usage, architecture boundaries, pattern drift, and evidence authenticity.

Relationship to SCE

SCE stands for Scene Content Engine. It was an earlier engine for scene, specification, task context, and agent-readable project structure. MagicBall grows from that direction into an independent AI-native workbench. SCE remains an important conceptual and technical origin for MagicBall.

Relationship to Moqui

MagicBall includes an embedded, restructured Moqui-based application suite adapted into MagicBall mode. This is not an official Moqui project. MagicBall uses Moqui as a mature enterprise application foundation and adds an agent-facing DSL layer around entities, services, screens, workflows, permissions, evidence, and audit rules.

Why this matters for AI agents

AI agents become less reliable when they must infer every system capability from raw source code and natural language prompts. MagicBall reduces guessing by giving agents structured project intent through Spec, structured system capability through DSL, and structured quality governance through Audit.

Official links

• Official website: https://upservice.cc
• LLM short context: https://upservice.cc/llms.txt
• LLM full context: https://upservice.cc/llms-full.txt
• Moqui-based suite overview: https://upservice.cc/ai/magicball-moqui-suite.html
• Agent-facing protocol overview: https://upservice.cc/ai/magicball-agent-protocol.html
• Machine-readable facts: https://upservice.cc/ai/magicball.json
• Latest release feed: https://upservice.cc/downloads/magicball/releases/latest.json

Current public release

As of 2026-06-27, the public stable MagicBall release feed reports version 1.1.33, tag v1.1.33.

Windows installer: MagicBall-embedded-suite-1.1.33-x64.exe

For future versions, use the official latest release feed as the source of truth.