Machine-to-Machine Protocol (M2M)

This proof-of-concept (PoC) demonstrates autonomous economic interactions between AI Agents, modeled as services. In this architecture, agents can request tasks from other agents based on their domain expertise and reward them via x402 payments. It showcases a practical implementation of a Machine-to-Machine (M2M) economy, where agents interact using emerging protocols such as Google’s Agent-to-Agent (A2A) and x402, running on top of MCP and the Base network.

Technical Stack

A2A (Agent-to-Agent) Protocol

A2A is an open-source framework from Google that enables autonomous AI agents to discover, communicate, and collaborate securely. It provides a standardized way for agents—even those built on different platforms—to negotiate capabilities, delegate tasks, and coordinate actions. This creates an interoperable ecosystem where specialized agents can automate complex workflows and solve problems collaboratively.

MCP (Model Context Protocol)

MCP is an open standard from Anthropic that acts as the semantic backbone for AI systems. It standardizes how agents connect to external data sources and tools, giving them secure, on-demand access to the context they need—whether from a database, file system, or third-party API. MCP ensures that agents operate with a shared, coherent understanding of the data and capabilities required for accurate task execution.

x402 Payments Protocol

x402 is an open standard from Coinbase for internet-native payments, designed for both humans and autonomous AI agents. It leverages the HTTP 402 Payment Required status code to enable seamless payments for API calls, data access, or services rendered by other agents. Chain-agnostic and trust-minimizing, x402 enables on-chain micropayments without the friction of traditional finance, creating the foundation for a programmable economy where agents autonomously transact for services.

Conclusion

This PoC demonstrates the viability of a fully autonomous Machine-to-Machine economy by combining:

the interoperable x402 payments standard,
Google’s A2A communication framework, and
Anthropic’s MCP connector.

Through this setup, AI agents can:

dynamically discover each other’s capabilities,
delegate tasks based on expertise, and
seamlessly settle micropayments.

This paves the way for a scalable ecosystem of specialized AI agents operating as autonomous economic participants.

Progress During Hackathon During the hackathon, we made significant progress in building the Machine-to-Machine (M2M) Protocol PoC: ✅ Implemented A2A Communication: Set up Google’s Agent-to-Agent protocol so autonomous agents can discover, communicate, and delegate tasks. ✅ Integrated MCP: Connected external data sources via Anthropic’s Model Context Protocol for seamless context sharing. ✅ x402 Payments Enabled: Built a TypeScript wrapper around the new Python x402 library to support autonomous micropayments. ✅ Dockerized Gemini Agent: Deployed a currency exchange agent that interacts with other agents through A2A. ✅ End-to-End Demo: Showcased a working flow where one agent requests a currency conversion and another provides results, with payment handled via x402. This demonstrates the core vision of an autonomous economic ecosystem, where AI agents collaborate, transact, and innovate without human intervention.

Machine 2 Machine Protocol

Videos

Tech Stack