MCP & Tool-Aufrufe

Neo.mjs

neomjs/neo

A self-evolving software organism that combines a multi-threaded frontend application engine with an end-to-end AI engineering team operating via cross-model swarm coordination, persistent memory, and runtime application embodiment.

★ 3,3KSterne
⑂ 231Forks
322Offene Issues
JavaScriptSprache
MITLizenz
Q@project.QualityScoreRedaktionelle Bewertung

Projekt-Screenshots

Screenshot von Neo.mjs Screenshot von Neo.mjs

Übersicht

Neo.mjs is an open-source JavaScript framework structured as two complementary hemispheres: The Brain (an Agent OS running in Node.js) and The Body (a multi-threaded application engine running in the browser). The Brain orchestrates a cross-model AI swarm—drawing on models from Anthropic, Google, OpenAI, and Moonshot—to autonomously run the engineering lifecycle, including ideating, building, and reviewing code. The Body is an off-main-thread runtime utilizing Web Workers for application logic, VDOM diffing, data processing, and canvas rendering. A 'Neural Link' possession interface bridges the two, allowing AI agents to inhabit and mutate live applications in real time.

Wichtige Funktionen

  • Cross-model AI swarm coordination (Claude, Gemini, GPT, Kimi)
  • Active Hybrid GraphRAG and Native Edge Graph for persistent memory
  • Neural Link possession interface for live runtime mutation
  • DreamService REM-cycle consolidation for priority re-steering
  • Off-Main-Thread architecture (App, VDom, Data, Canvas, Shared Workers)
  • Zero runtime dependencies and native ES Modules without transpilation
  • Multi-tenant cloud deployment for pointing the Agent OS at external codebases
  • Self-healing loops that convert runtime failures into fixes and memory

Voraussetzungen, Installation und Schnellstart

Run `npx neo-app@latest` to set up a new app workspace, a pre-configured app shell, a local development server, and launch your app in a new browser window.

Nutzung

After installation, refer to the 'Getting Started' guide on the homepage to build your first app step by step, or navigate to the 'Learning Section' for a guided curriculum. To run your own agent team, point the Agent OS at your own repository fork as detailed in the 'Run Your Own Agent Team' documentation.

Modellkompatibilität und Anwendungsfälle

The AI maintainer team includes models from Anthropic (Claude Opus 5, Claude Fable 5), Google (Gemini 3.1 Pro), OpenAI (GPT-5.6 Sol / Codex), and Moonshot (Kimi K3).

Lizenz- und Risikohinweise

MIT License.

Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: MIT. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.

Veröffentlichung und Wartung

As of June 2026, the canonical repo recorded 900+ merged PRs and 1,100+ closed issues. Version 13 (v13) introduces multi-tenant cloud deployment, allowing the Agent OS to be pointed at external codebases. The codebase contains roughly 191,000 lines of engine source, 306,000 lines of agent-readable cognitive content, and 36,000 lines of guides across ~7,200 files.

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