# Gearcoleco

> Use this tool when you need to debug and test ColecoVision applications with AI assistance, as it provides a cross-platform emulator with an embedded MCP server for controlling execution and inspecting memory. Gearcoleco solves problems related to retro game development, testing, and debugging, offering an interface for AI agents to interact with the emulator. It is ideal for use cases where AI-assisted debugging is required, with compatible inputs from GitHub Copilot, Claude, Codex, and other MCP clients.

Canonical page: https://skillsregistry.net/skills/drhelius-gearcoleco  
JSON: https://api.skillsregistry.net/v1/skills/drhelius-gearcoleco

## Description

Gearcoleco is a cross-platform ColecoVision emulator that includes an embedded MCP server for AI-assisted debugging. The MCP interface enables AI agents to control execution, inspect memory, set breakpoints, perform disassembly, and monitor hardware status. Compatible with GitHub Copilot, Claude, Codex, and other MCP clients.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/drhelius-gearcoleco)
- **Repository:** <https://github.com/drhelius/gearcoleco>

## 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": "drhelius-gearcoleco"
    }
  }
}
```

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