# Commodore 64 Ultimate MCP Server

> Commodore 64 Ultimate MCP Server — martijn-devrev-ultimate64mcp. Use this tool when you need to control and interact with Commodore 64 Ultimate hardware remotely, solving problems such as automating retro computing tasks and integrating vintage systems with modern AI assistants. It accepts natural language commands as input and provides outputs through a REST API, enabling program execution, memory operations, and device configuration. Ideal for use cases requiring automated control of retro hardware, such as retro gaming, demoscene development, and vintage computer emulation.

Canonical page: https://skillsregistry.net/skills/martijn-devrev-ultimate64mcp  
JSON: https://api.skillsregistry.net/v1/skills/martijn-devrev-ultimate64mcp

## Description

Enables AI assistants to control Commodore 64 Ultimate hardware via REST API, supporting program execution, memory operations, disk management, audio playback, and device configuration through natural language commands.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bqh8g698vi)
- **Repository:** <https://github.com/mbosschaart/Ultimate64MCP>

## 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": "martijn-devrev-ultimate64mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/martijn-devrev-ultimate64mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/martijn-devrev-ultimate64mcp/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