# pc-screen-control

> pc-screen-control — noncellular-dumpiness647-pc-screen-control. Use this tool when you need to connect your Windows screen to AI models as structured data, solving integration and automation challenges for tasks like screen scraping and automated testing. It takes Windows screen data as input and outputs structured data for AI models, compatible with Claude Desktop and other MCP clients. Ideal for use cases requiring automated data extraction and processing from Windows screens.

Canonical page: https://skillsregistry.net/skills/noncellular-dumpiness647-pc-screen-control  
JSON: https://api.skillsregistry.net/v1/skills/noncellular-dumpiness647-pc-screen-control

## Description

Connect your Windows screen to AI models as structured data using this MCP server for Claude Desktop and other MCP clients.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Noncellular-dumpiness647/pc-screen-control)

## 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": "noncellular-dumpiness647-pc-screen-control"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/noncellular-dumpiness647-pc-screen-control` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/noncellular-dumpiness647-pc-screen-control/pull`

---
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