# cffbrw-mcp

> cffbrw-mcp — shizlie-cffbrw-mcp. Use this tool when you need to compile AI workflows for Cloudflare edge, solving issues of workflow optimization and edge computing. It takes in AI workflow code and outputs compiled workflows, integrating with git for version control. Ideal for use cases requiring efficient edge AI deployment and management.

Canonical page: https://skillsregistry.net/skills/shizlie-cffbrw-mcp  
JSON: https://api.skillsregistry.net/v1/skills/shizlie-cffbrw-mcp

## Description

MCP server for CFFBRW — AI workflow compiler for Cloudflare edge

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/shizlie/cffbrw-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": "shizlie-cffbrw-mcp"
    }
  }
}
```

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