# Machine 2 Machine Protocol

> Use this tool when you need to facilitate autonomous interactions between AI agents, enabling them to request services and conduct micropayments in a decentralized Machine-to-Machine economy. It solves problems of agent communication, context management, and secure payment processing, providing a seamless interface for agents to exchange services and value. Ideal for use cases requiring decentralized, trustless, and efficient machine-to-machine transactions, with inputs including service requests and outputs including compensated service delivery.

Canonical page: https://skillsregistry.net/skills/andrearettaroli-m2m  
JSON: https://api.skillsregistry.net/v1/skills/andrearettaroli-m2m

## Description

Enables AI agents to autonomously request services from other specialized agents and compensate them via x402 micropayments. Demonstrates a Machine-to-Machine economy using A2A protocol for agent communication, MCP for context management, and blockchain-based payments on Base network.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** finance
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/eyzdddhg3y)
- **Repository:** <https://github.com/AndreaRettaroli/m2m>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "andrearettaroli-m2m"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/andrearettaroli-m2m` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/andrearettaroli-m2m/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt