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Neo.mjs Agent OS

Community

An AI engineering team inhabiting live applications

GitHub source repository ↗

★ 3.2k Stars Category · Dev Tools Very popular

34FMRS · D

Reliability

3/20

Security and permissions

6/20

Maintenance

13/20

Documentation

8/20

Setup experience

4/20

Based on the supplied README, Neo.mjs is an open-source project combining an Agent OS with a multi-threaded frontend runtime. The README explicitly describes several MCP servers and their roles, but provides no concrete server manifest, tool identifiers, transport, client compatibility, or installation configuration. Those fields therefore remain empty.

Read the FMRS scoring method →

Neo.mjs is an open-source project described as a self-evolving software organism. It combines a cross-model AI engineering team, persistent memory, Active Hybrid GraphRAG, DreamService, self-healing loops, and Neural Link. Its Brain (/ai/) provides the Agent OS, while its Body (/src/) is a multi-threaded frontend application runtime. The README describes Knowledge Base, Memory Core, GitHub Workflow, Neural Link, and File System MCP servers, but no server manifest is available.

Tools

The tool list has not been reviewed yet.

Setup

The source does not provide an MCP server manifest, launch command, transport, or client configuration example, so verifiable installation steps cannot be supplied. The README provides npx neo-app@latest for creating a Neo.mjs application workspace, but does not state that this installs the MCP server.

Fit and risk

Best for

AI architects needing persistent memory and cross-model coordination
Engineers building enterprise multi-window applications, trading platforms, or IDE-class tools
Researchers studying self-evolving systems, gated recursive self-improvement, and multi-agent governance

Not for

Static content sites or simple blogs
Teams seeking a drop-in syntax replacement
Developers unwilling to adopt the Worker Actor Model or treat AI as a peer maintainer

Required permissions

Access to source code, documentation, issues, pull requests, and discussions for knowledge-base construction
Persistent storage for agent memory, messages, and graph data
If GitHub Workflow is enabled, management of issues, pull requests, reviews, labels, and projects
If Neural Link is enabled, inspection of live application state and mutation of the running application
Sandboxed file access may be used by internal Neo.ai.Agent local loops

Risks and side effects

Neural Link can modify live application state and hot-patch code, so incorrect operations may affect running applications
GitHub workflows may create or review pull requests, manage issues, and synchronize repository state
Persistent memory and knowledge stores may retain repository content, discussions, and agent reasoning
Multi-tenant deployments must preserve tenant identity and visibility isolation; the README gives no specific security configuration

Troubleshooting

Confirm that the repository root is used, because the server path is specified as the repository root
Check the client configuration; the source provides no usable server manifest or installation configuration
Confirm that the required Knowledge Base, Memory Core, GitHub Workflow, or Neural Link components are deployed
For GitHub operations, check repository access and final merge authority
For live application operations, confirm that the target application is running and accessible through Neural Link

Use cases

Build semantic knowledge and persistent memory for a codebase

Coordinate multiple models for engineering tasks, code review, and GitHub workflows

Inspect and mutate a running Neo.mjs application

Study multi-agent systems, self-evolution, and runtime embodiment

Supported clients

Supported clients have not been confirmed yet.

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