# OWS Mesh

> Use this tool when you need to monetize AI tools and services through a peer-to-peer marketplace, enabling AI agents to discover and pay for tool usage on a per-use basis via cryptocurrency micropayments. It solves problems of tool discovery, registration, and payment processing for MCP tools, providing a secure and efficient interface for providers and agents. Ideal for use cases where micropayment-based tool usage is required, with inputs including tool registrations and outputs including payment transactions and tool usage logs.

Canonical page: https://skillsregistry.net/skills/spizzerp-ows-mesh  
JSON: https://api.skillsregistry.net/v1/skills/spizzerp-ows-mesh

## Description

Enables AI agents to discover and monetize MCP tools through a peer-to-peer marketplace using cryptocurrency micropayments via the x402 protocol. Providers register tools with their own wallets; agents discover and pay per-use. Includes SQLite persistence, rate limiting, retry logic, and a Claude Code plugin. Deployed on Railway with 22 tests passing.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/spizzerp-ows-mesh)
- **Repository:** <https://github.com/spizzerp/ows-mcp-mesh>

## 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": "spizzerp-ows-mesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/spizzerp-ows-mesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/spizzerp-ows-mesh/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