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arian-gogani/nobulex

by Various

The trust economy for autonomous AI agents. Credit scores for machines. Agents earn Trust Capital through verified behavior, gating what they are allowed to do. Autonomy earned, no

A

MCP

arian-gogani/nobulex

Added 1 June 2026

#accountability #agent-governance #ai-agents #ai-security #autonomous-agents #compliance #credit-score #cryptography

Overview

Nobulex is a trust economy for autonomous AI agents, assigning credit scores to machines. Agents earn Trust Capital through verified behavior, which gates their allowed actions. Autonomy is earned, not granted, based on this reputation system.

Best for

Best for
Developers experimenting with reputation-based agent autonomy

Use cases

  • Gating agent actions based on earned trust scores
  • Building reputation systems for multi-agent ecosystems
  • Enforcing behavior-based access controls in autonomous systems

How to use

Install

npx tsx examples/trust-capital-demo.ts

Tools exposed

  • web_search
  • get_weather

Notes

Nobulex is a trust economy for autonomous AI agents, assigning credit scores to machines. Agents earn Trust Capital through verified behavior, which gates their allowed actions. Autonomy is earned, not granted, based on this reputation system.

31 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Gating agent actions based on earned trust scores
  • Building reputation systems for multi-agent ecosystems
  • Enforcing behavior-based access controls in autonomous systems

Pros

  • Novel approach to agent governance via earned trust
  • TypeScript codebase for easy integration with modern stacks
  • Open source with a clear, focused concept

Cons

  • Very early stage with only 31 GitHub stars
  • Limited documentation and community support
  • Unproven in production environments

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Novel approach to agent governance via earned trust
  • TypeScript codebase for easy integration with modern stacks
  • Open source with a clear, focused concept

Cons

  • Very early stage with only 31 GitHub stars
  • Limited documentation and community support
  • Unproven in production environments
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