# Handyman-MCP

> Handyman-MCP — kennetchau-handyman-mcp. Use this tool when you need to manage stateful AI agent infrastructure with persistent memory and secure execution. It solves problems related to data persistence and sandboxed environments for AI models, providing a reliable interface for inputs such as git repositories and outputs like executable models. Ideal for use cases requiring secure and efficient AI model deployment and management.

Canonical page: https://skillsregistry.net/skills/kennetchau-handyman-mcp  
JSON: https://api.skillsregistry.net/v1/skills/kennetchau-handyman-mcp

## Description

Stateful AI Agent Infrastructure with Persistent FTS5 Memory and Sandboxed Execution.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/kennetchau/Handyman-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": "kennetchau-handyman-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kennetchau-handyman-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kennetchau-handyman-mcp/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