# fizzy-mcp

> fizzy-mcp — fabric-pro-fizzy-mcp. Use this tool when you need to manage model contexts and integrate with Git for version control, solving problems related to model management and collaboration. It provides a server for Fizzy's Model Context Protocol, accepting inputs such as model updates and Git repository changes, and outputs synchronized model contexts. Ideal for use cases involving machine learning model development and deployment.

Canonical page: https://skillsregistry.net/skills/fabric-pro-fizzy-mcp  
JSON: https://api.skillsregistry.net/v1/skills/fabric-pro-fizzy-mcp

## Description

Model Context Protocol Server for Fizzy

## Trust

- **Trust score (0–1):** 0.76
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Fabric-Pro/fizzy-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": "fabric-pro-fizzy-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fabric-pro-fizzy-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fabric-pro-fizzy-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