# Peggle AI MCP Server

> Use this tool when you need to automate gameplay in Peggle, capturing screen data and simulating user interactions to enable AI models to play the game. It solves problems related to game automation, providing visual analysis and coordinate-based interaction capabilities. The tool takes screen data as input and outputs simulated mouse clicks, ideal for use cases requiring autonomous gameplay in Peggle.

Canonical page: https://skillsregistry.net/skills/collabvmgamez-peggle-ai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/collabvmgamez-peggle-ai-mcp

## Description

Enables AI models to play the game Peggle by capturing the primary monitor's screen and simulating mouse clicks. It provides tools for visual analysis and coordinate-based interaction to automate gameplay.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/geunj6qajw)
- **Repository:** <https://github.com/CollabVMgamez/peggle-ai-mcp>

## 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": "collabvmgamez-peggle-ai-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/collabvmgamez-peggle-ai-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/collabvmgamez-peggle-ai-mcp/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