neuromesh — security grade SAFE, quality 67/100

Security audit verdict: SAFE · quality 67/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by pinoox · MCP Server · ★ 90

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is neuromesh safe to install? View the security audit →

About neuromesh

NeuroMesh Don’t delete the extra code. Fold it. How does nature pack two metres of DNA into a nucleus without deleting a single letter? Not by throwing genes away — by folding. NeuroMesh does the same thing to your repository: a neural graph in RAM, reversible one-line folds, and an evidence packet instead of three thousand-line files dumped into Cursor or Claude. Local-first MCP · Cursor · Codex · OpenCode · MiMo CLI · Antigravity · VS Code · Claude · Kilo · Trae · Windsurf · Zed The pain · The idea · Galaxy · Install · Connect · Docs · Site The pain You ask a simple question in a large project. The editor copies two or three thousand

antigravityclaude-codecodecode-analysiscode-intelligencecodexcontext-managementcursordeveloper-toolsgemini-cli

Quick Facts

Stars90
Forks8
LanguageRust
CategoryMCP Server
LicenseMIT
Quality Score66.5721735384173/100
Open Issues1
Last Updated2026-09-16
Created2026-08-22
Platformsclaude-code, cli, codex, gemini, mcp, rust
Est. Tokens~25k

Compatible Skills

These tools work well together with neuromesh for enhanced workflows:

  • splitrail — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • compass — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (60%)
  • homebrew-pandafilter — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)

neuromesh alternative? Top 6 similar tools

Looking for a neuromesh alternative? If you're comparing neuromesh with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • sub-agents-mcp by shinpr · ⭐ 98

    Define task-specific AI sub-agents in Markdown for any MCP-compatible tool.

  • omega-memory by omega-memory · ⭐ 218

    Persistent memory for AI coding agents

  • agent-skills by jdrhyne · ⭐ 241

    A collection of AI agent skills for Clawdbot, Claude Code, Codex

  • mcp-fusion by vinkius-labs · ⭐ 204

    MCP Fusion - The framework for AI-native MCP servers.

  • awesome-ai-agent-skills by seb1n · ⭐ 149

    103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf,

  • deep-code-reasoning-mcp by haasonsaas · ⭐ 102

    A Model Context Protocol (MCP) server that provides advanced code analysis and reasoning capabilities powered

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Frequently Asked Questions

What is neuromesh?

neuromesh is The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants. It is categorized as a MCP Server with 90 GitHub stars.

What programming language is neuromesh written in?

neuromesh is primarily written in Rust. It covers topics such as antigravity, claude-code, code.

How do I install or use neuromesh?

You can find installation instructions and usage details in the neuromesh GitHub repository at github.com/pinoox/neuromesh. The project has 90 stars and 8 forks, indicating an active community.

What license does neuromesh use?

neuromesh is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to neuromesh?

The top alternatives to neuromesh on Agent Skills Hub include sub-agents-mcp, omega-memory, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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