Skillget

multiagent-visibility-tool

agent
Guvenlik Denetimi
Basarisiz
Health Gecti
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 12 GitHub stars
Code Basarisiz
  • process.env — Environment variable access in agentscope/agentscope.js
  • network request — Outbound network request in agentscope/agentscope.js
  • child_process — Shell command execution capability in bin/visibility.js
  • execSync — Synchronous shell command execution in bin/visibility.js
  • process.env — Environment variable access in bin/visibility.js
  • process.env — Environment variable access in src/server.js
  • fs module — File system access in src/server.js
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This tool provides DevOps-style observability for multi-agent AI systems. It allows developers to trace, visualize, and debug agent workflows and inter-agent messages in real time via a local dashboard.

Security Assessment
Overall Risk: High. The tool heavily interacts with the underlying system, presenting significant security concerns. It utilizes synchronous shell command execution (`execSync`) and general child process capabilities, which could be highly vulnerable to command injection if exploited. Additionally, it makes outbound network requests, accesses environment variables, and reads the file system. It does not request explicit dangerous permissions, but the hardcoded capabilities within the JavaScript code require strict scrutiny. No hardcoded secrets were detected.

Quality Assessment
The project appears active and is recently maintained, with its last push occurring today. It is properly licensed under the permissive MIT standard. However, community trust and adoption are currently very low, reflected by only 12 GitHub stars. The documentation is well-written and clear, though the listed compatible CLIs remain unspecified.

Verdict
Use with caution — while the utility is useful, the inclusion of synchronous shell execution and broad file/network access requires a thorough security review of your deployment environment before integrating.
SUMMARY

DevTools for multi-agent AI — trace, visualize and debug agent workflows in real time

README.md

🔍 MAVT — Multi-Agent Visibility Tool

The missing DevTools for multi-agent AI systems.

PyPI
License: MIT
Stars

MAVT Demo

You wouldn't ship a backend without logs. Why are you shipping agents blind?

Multi-agent systems are the future of AI — but right now, debugging them feels like
reading smoke signals. MAVT gives you full observability: every agent call, every
decision step, every inter-agent message, visualized in real time.

The problem

You build a multi-agent workflow. Something breaks. You ask yourself:

  • Which agent failed — and why?
  • What did agent A actually say to agent B?
  • Where in the chain did the task go wrong?
  • Why is this running so slow?

You open your terminal. You see... nothing useful.

MAVT fixes this.

What you get
🔁 Agent-to-agent traces See every message passed between agents, in order
🧠 Decision step inspector Understand what reasoning led to each action
📊 Live workflow graph Visual execution graph, updating in real time
⏱ Execution timeline Spot bottlenecks and latency across your pipeline
🐛 Real-time debug view No post-hoc log parsing — watch it live

Get started in 60 seconds

pip install mavt

from mavt import track_agents

track_agents()  # That's it.

Open your browser → http://localhost:7777

Your agents are now fully observable.

Works with

  • ✅ AgentScope — supported now
  • 🔜 LangChain — coming soon
  • 🔜 AutoGen — coming soon
  • 🔜 CrewAI — coming soon
  • 🔜 Custom agents — bring your own

Why observability is non-negotiable

"If you can't measure it, you can't manage it."

AI agents are making real decisions in production systems today — in customer service,
in code generation, in enterprise workflows. Without visibility:

  • You can't debug failures
  • You can't trust outputs
  • You can't scale safely
  • You can't explain decisions to stakeholders

MAVT is the foundation layer your agent stack is missing.

Roadmap

  • AgentScope integration
  • Live workflow graph
  • Agent-to-agent message tracing
  • LangChain integration
  • AutoGen integration
  • CrewAI integration
  • Metrics & cost tracking per agent
  • Export traces to JSON / OpenTelemetry
  • Cloud-hosted dashboard (optional)

Contributing

Issues, PRs, and framework integrations are very welcome.
If you're using MAVT with a framework not listed above — open an issue and let's add it.

Star history

If MAVT saves you a debugging session, consider leaving a ⭐ —
it helps other developers find the tool.

About the author

Built by Hitarth Bhatt — AI product leader with 10+ years
shipping AI systems at scale. MAVT grew out of a real frustration: the more powerful
multi-agent systems become, the harder they are to see inside.

MIT License · PyPI · Issues

Yorumlar (0)

Sonuc bulunamadi