# Meta-Stamp Pockets

> Use this tool when you need to access paywalled creator content, such as videos, while ensuring creators receive automatic micropayments for each content pull. Meta-Stamp Pockets solves the problem of content monetization for creators, providing a patent-pending infrastructure for AI agents to pay for accessed content. It takes AI requests as input and outputs paywalled content, with creators receiving $0.0025 per pull, making it ideal for use cases where licensed content is required.

Canonical page: https://skillsregistry.net/skills/chriscoynetalent-yhjh-meta-stamp-pockets  
JSON: https://api.skillsregistry.net/v1/skills/chriscoynetalent-yhjh-meta-stamp-pockets

## Description

The first commercial implementation of HTTP 402 Payment Required for creator content monetization. AI agents pay $0.0025 per content pull from paywalled creator libraries. Patent-pending micropayment infrastructure — creators get paid automatically every time AI accesses their content. 1,800+ Dhar Mann videos indexed and paywalled.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** finance
- **Updated:** 2026-05-13

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/chriscoynetalent-yhjh/meta-stamp-pockets)

## 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": "chriscoynetalent-yhjh-meta-stamp-pockets"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/chriscoynetalent-yhjh-meta-stamp-pockets` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/chriscoynetalent-yhjh-meta-stamp-pockets/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