# Screeny MCP Server

> Use this tool when you need to capture application window screenshots for development and debugging purposes, enabling AI agents to access visual data while maintaining user privacy. It solves problems related to automated testing, UI validation, and debugging, allowing for efficient issue resolution. The Screeny MCP Server takes application window identifiers as input and outputs captured screenshots, making it a valuable asset in macOS development environments.

Canonical page: https://skillsregistry.net/skills/rohanrav-screeny  
JSON: https://api.skillsregistry.net/v1/skills/rohanrav-screeny

## Description

A privacy-first macOS MCP server that enables AI agents to capture screenshots of pre-approved application windows for development and debugging tasks.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/zqsvkhpcey)
- **Repository:** <https://github.com/rohanrav/screeny>

## 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": "rohanrav-screeny"
    }
  }
}
```

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