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r/CustomAI

▲ 3 r/CustomAI+2 crossposts

I’ve been working on an open-source security tool to sandbox AI agents/MCP servers, and I'd love to know if you find it useful.

Hey everyone! 👋

With tools like Cursor, Claude Desktop, and various MCP servers becoming part of our daily workflows, I started worrying a bit about the attack surface of having autonomous, stateful AI agents running locally. What happens if an agent pulls down a poisoned package or executes a malicious tool?

To try and solve this for myself, I built W.H.Agent (White Hat Agent). It’s an open-source CLI and sandboxing tool designed to act as a pre-execution and runtime defense for AI agents.

To be completely honest, it’s still very much a work in progress (the OS-native sandboxing is currently macOS-only, for example), and I’m sure there are edge cases I haven't even thought of yet. But I decided to open-source it today because I genuinely want to see if this approach brings value to other developers.

A few things it currently does:

  • Global Auto-Discovery: Scans your machine to find where agents/MCP servers are installed.
  • AST Taint Tracking: Parses agent scripts to detect data exfiltration before it runs.
  • OS-Native Sandboxing: Wraps execution in sub-millisecond sandboxes (using macOS Seatbelt profiles currently) instead of heavy Docker containers.
  • Secure npm Installs: Checks for typosquatting and supply chain risks.

I figured the best way to learn and improve it is to put it out there. If you have a few minutes, I would be incredibly grateful if you checked it out or gave it a quick roast. Is this something you would use in your workflow?

Thanks so much for your time, and I'm looking forward to any feedback (the good, the bad, and the ugly)!

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u/Additional-Elk-6 — 2 days ago
▲ 24 r/CustomAI+1 crossposts

Tired of flat Mermaid flowcharts but hate manually aligning 2.5D isometric grids in Figma, so I built a local-first compiler in Go.

Getting LLMs to draw architecture diagrams is usually a nightmare. If you ask them to write raw SVG, they hallucinate coordinates and make a mess. If you ask them to write Mermaid, you get flat, boring 2D boxes.

I built iso-topology—a Go compiler and MCP server designed specifically to let AI agents render designer-grade, 2.5D isometric diagrams directly from your chat prompt.

The "Prompt to Diagram" Workflow

You don't write YAML. You just prompt your AI agent (like Claude Code or Cursor): "Draw a dark-mode RAG pipeline. Put a glowing vector database in the center, and connect it to a gateway behind it."

The AI agent then runs a robust 3-step loop under the hood:

  1. Discover (capabilities): The AI queries the CLI to see what shapes, styles (gradients, glows, textures), and 200+ brand icons are available.
  2. Lint & Solve (validate): The AI writes a relative DSL (no coordinate math, just place: {behind: gateway}). The Go compiler validates it and tells the AI if it made typos or layout overlaps, with automatic fix suggestions.
  3. Render: Once validated, it compiles into a high-fidelity 2.5D SVG and an interactive HTML viewer.

Key Highlights

  • Fully local & private: Written in Go, compiles to a single static binary. No external cloud dependencies or API keys required.
  • Ready-to-use MCP Server: You can register it to Claude Desktop or Cursor in one line: claude mcp add isotopo -- isotopo-mcp
  • 100% Deterministic: Perfect for Git. The same YAML output from the AI always renders the exact same SVG byte-for-byte, making it easy to review diagram changes in Git diffs.
  • Apache 2.0 Open Source.

👉 GitHub Repo: github.com/MarkovWangRR/iso-topology

How to test it locally:

# Install the compiler
go install github.com/MarkovWangRR/iso-topology/cmd/isotopo@latest

# Prompt your coding agent 
Install the skill https://github.com/MarkovWangRR/iso-topology/tree/main/skills and analyze the XXXX landing page's visual style, then draw a usecase dragram in 2.5s style based on iso-topology.
u/Creative_Factor8633 — 5 days ago