AgentPay OS

AgentPay OS enables autonomous AI agents to execute real, on-chain payments using MNEE, a USD-backed stablecoin on Ethereum, with programmable limits, escrow, and full transparency.

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Inspiration

As AI systems become more capable of reasoning and decision-making, we noticed a fundamental limitation: AI agents still cannot act economically on their own. Most AI workflows rely on centralized billing systems, API credits, or manual human approvals to handle payments. This breaks autonomy and limits real-world deployment.

We were inspired by the idea that money itself should be programmable, not just for humans, but for AI agents as well. The availability of MNEE, a USD-backed stablecoin on Ethereum, made it possible to design a system where AI agents can safely execute real financial actions with predictable value and full on-chain transparency.

What it does

AgentPay OS is a programmable money infrastructure that enables autonomous AI agents to transact using MNEE stablecoin on Ethereum.

The platform allows agents to:

Connect to Ethereum wallets and manage on-chain balances

Execute stablecoin payments programmatically

Enforce spending limits and safety controls

Use escrow contracts for secure, conditional settlement

Provide transparent, verifiable transactions via Etherscan

By combining AI decision-making with smart contract enforcement, AgentPay OS allows agents to act economically, not just generate outputs.

How we built it

AgentPay OS was built as a full-stack system:

Frontend: A React dashboard using wagmi and viem for wallet connectivity, balance display, and user interaction.

Backend: A Node.js and Express server that validates requests, enforces rules, and coordinates blockchain interactions.

Blockchain Layer: Solidity smart contracts deployed on Ethereum, interacting directly with the MNEE ERC-20 stablecoin to handle payments, limits, and escrow.

Demo Mode: A simulation layer that mirrors real API flows for testing without requiring wallets or real funds.

The system cleanly separates off-chain AI reasoning from on-chain value execution, ensuring both flexibility and security.

Challenges we ran into

One of the main challenges was designing safe autonomy. Allowing AI agents to control real funds requires strict safeguards, including spending limits and pause mechanisms enforced on-chain.

Another challenge was making complex blockchain interactions easy to understand in a short demo. We focused heavily on clarity, transparency, and verifiability so judges and users could quickly grasp how the system works.

Balancing technical depth with usability was also a key challenge, especially when integrating live wallet flows and demo-mode simulations.

Accomplishments that we're proud of

Building a working end-to-end prototype with real smart contract logic

Demonstrating autonomous AI-initiated stablecoin payments

Implementing programmable spending limits and escrow for safety

Delivering a clean, demo-ready interface with on-chain verification

Deep, meaningful integration of MNEE rather than superficial usage

What we learned

We learned that programmable money is a critical missing layer for autonomous AI systems. Stablecoins like MNEE are far better suited for agent economies than volatile assets due to their predictability.

We also learned that trust in AI-driven finance comes from on-chain enforcement and transparency, not from off-chain promises or centralized controls.

Finally, we learned the importance of clear system design and storytelling when presenting complex infrastructure projects.

What's next for AgentPay OS

Future directions for AgentPay OS include:

Multi-agent marketplaces with autonomous settlement

DAO-governed agent treasuries

Oracle-verified escrow release conditions

Integration with real AI services and data providers

Expansion to Layer-2 networks and cross-chain support

Our long-term vision is to enable a new class of autonomous, AI-driven economic systems powered by programmable money.

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