What is the 'Neural Link'?

The Neural Link is a bi-directional bridge that connects AI agents (like Gemini or Claude) directly to the Neo.mjs runtime. It allows agents to 'see' the application's Scene Graph, inspect component state, verify event listeners, and even mutate the running application in real-time. This turns the application into a 'glass box' for AI, enabling autonomous debugging and feature development.

Why is Neo.mjs called an 'Application Engine' instead of a framework?

Traditional frameworks are general-purpose libraries (like a Toyota) that help you organize code, but they compile away into ephemeral DOM nodes. Neo.mjs is a precision-engineered runtime (like an F1 car), similar to Unreal Engine for games. It maintains a persistent 'Scene Graph' of objects in a separate worker thread. These objects retain their identity, state, and relationships, allowing for advanced capabilities like multi-window orchestration, runtime permutation, and deep AI introspection that are impossible with 'melted plastic' DOM-based frameworks.

What is 'Context Engineering'?

Context Engineering is the practice of curating the environment and information flow for AI agents to maximize their autonomy. In Neo.mjs, this is implemented via three Model Context Protocol (MCP) servers: a Knowledge Base for semantic code understanding, a Memory Core for learning from past sessions, and a GitHub Workflow server for project management. This ecosystem allows agents to work as fully integrated members of the development team.

What is 'Object Permanence' in the context of Neo.mjs?

In Neo.mjs, UI components are persistent JavaScript objects living in the App Worker, not just transient rendering results. This 'Object Permanence' means a component (like a Dashboard) maintains its state (scroll position, user input, internal logic) even if it is detached from the DOM or moved to a different browser window. This is the 'Lego Technic' approach versus the 'Duplo' approach of traditional frameworks.

What is an 'Agent Operating System'?

Neo.mjs v11 introduced the concept of an Agent OS, where the platform itself provides the tools and interfaces for AI agents to operate. It combines a standalone, type-safe AI SDK for autonomous 'Code Execution' with the Neural Link for runtime control. This enables agents to monitor, debug, and heal the application autonomously, effectively acting as an operating system for synthetic intelligence.

How does Neo.mjs handle multi-window applications?

Neo.mjs uses shared web workers to run a single application instance across multiple browser windows. All windows share the same application state and data in real-time. Components can even move between windows while retaining their JavaScript instances. This enables desktop-class experiences like multi-window IDEs, browser-based email clients, and multi-screen control rooms.

What makes Neo.mjs different from React, Angular, or Vue?

Neo.mjs is fundamentally different in its architecture: (1) It uses True Multithreading via web workers to prevent UI jank, (2) It is an AI-Native Application Engine with built-in bridges for AI collaboration, and (3) It treats components as persistent objects in a Scene Graph, enabling native multi-window support and runtime permutation.

Frontmatter

id	7464
title	MCP Server: Refine Memory Server Endpoints
state	Closed
labels	enhancementhacktoberfestai
assignees	Aki-07
createdAt	Oct 11, 2025, 8:02 PM
updatedAt	Oct 13, 2025, 9:26 PM
githubUrl	https://github.com/neomjs/neo/issues/7464
author	tobiu
commentsCount	2
parentIssue	7399
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Oct 13, 2025, 9:26 PM

MCP Server: Refine Memory Server Endpoints

Name: Neo.mjs Application Engine
Author: Neo.mjs

Closed v11.0.0 enhancementhacktoberfestai

tobiu commented on Oct 11, 2025, 8:02 PM

This ticket is for polishing and refining the recently implemented memory and summary endpoints in the Memory Core MCP server. It addresses several minor points that will improve code consistency, cleanliness, and maintainability.

Acceptance Criteria

Consistent Service Method Return Structures:
- The queryMemories and querySummaries service methods should return a results property (e.g., { count: number, results: object[] }) to align with the final API response structure.
Numeric Default Pagination Values:
- Update the route handlers in memories.mjs and summaries.mjs to use numeric default values for limit and offset instead of strings.
Externalize allowedCategories:
- The hardcoded allowedCategories array in ai/mcp/server/memory/routes/summaries.mjs should be moved to a more centralized location, such as the config.mjs file, to make it easier to manage.

Agent Instructions

To work on this ticket, please start your session with the following prompt:

Please follow the instructions in @AGENTS.md.

Once you are initialized, I want to work on a sub-task for the "Architect AI Tooling as a Model Context Protocol (MCP) Servers" epic.

My task is to implement: MCP Server: Refine Memory Server Endpoints

You will need to read the epic context from @.github/ISSUE/epic-architect-ai-tooling-as-mcp.md and the specific ticket details from @.github/ISSUE/ticket-refine-memory-server-endpoints.md before we begin.

tobiu assigned to @tobiu on Oct 11, 2025, 8:02 PM

tobiu added parent issue #7399 on Oct 11, 2025, 8:03 PM

tobiu added the enhancement label on Oct 11, 2025, 8:03 PM

tobiu added the ai label on Oct 11, 2025, 8:03 PM

tobiu cross-referenced by PR #7463 on Oct 11, 2025, 8:06 PM

tobiu unassigned from @tobiu on Oct 11, 2025, 8:45 PM

tobiu assigned to @Aki-07 on Oct 11, 2025, 8:45 PM

tobiu added the hacktoberfest label on Oct 11, 2025, 8:45 PM

tobiu Oct 11, 2025, 8:45 PM

sure.

2025-10-12T03:13:51Z @Aki-07 cross-referenced by PR #7466

tobiu closed this issue on Oct 13, 2025, 9:26 PM