CFFBRW — AI Workflow Compiler for Cloudflare Edge

CFFBRW MCP Server

Agents think once. CFFBRW runs forever.

CFFBRW is an AI-powered workflow compiler for Cloudflare's edge. Write automation in plain English markdown — or compile execution plans via MCP. CFFBRW runs them deterministically on Cloudflare Workers, Durable Objects, D1, KV, and R2. No AI tokens at runtime. Self-healing.

This repo provides the MCP server configuration for connecting AI agents (Claude Code, Cursor, Windsurf, ChatGPT, Copilot) to CFFBRW.

Quick Setup

Claude Code

Add to .mcp.json in your project root:

{
  "mcpServers": {
    "cffbrw": {
      "type": "url",
      "url": "https://api.cffbrw.com/mcp",
      "headers": {
        "Authorization": "Bearer wfk_your_key_here",
        "Accept": "application/json, text/event-stream"
      }
    }
  }
}

Cursor / Windsurf

Same .mcp.json format. Place in your project root or configure via the editor's MCP settings.

ChatGPT / Copilot (OAuth)

Use the MCP server URL https://api.cffbrw.com/mcp — the client handles OAuth redirect.

Get an API Key

1. Sign up at cffbrw.com
2. Go to API Keys
3. Create a key — you'll get wfk_...

What You Get

14 tools, 4 resources, 2 prompts.

Tools

Tool	Description
deploy_workflow	Create a new workflow with name, markdown, and compiled plan
update_workflow	Update an existing workflow's markdown and/or plan
publish_workflow	Make a workflow live for API triggers and cron
unpublish_workflow	Revert to draft
list_workflows	List all workflows in the workspace
get_workflow	Get workflow details (markdown, plan, status)
validate_plan	Validate a plan JSON — resolves connector intents + 9 semantic checks. Free.
prevalidate_markdown	AI screens markdown for issues before compilation
run_workflow	Execute a workflow, returns run ID
get_run_status	Get run status with step outputs
list_runs	List runs for a workflow
schedule_workflow	Set a cron schedule
unschedule_workflow	Remove the cron schedule

Resources

Resource	What your model learns
Execution Plan Schema	The exact JSON format for plans
Step Types	How to configure each of the 11 step types
Available Tools	MCP tools registered in your workspace
Example Plans	Correct patterns from simple to complex

Prompts

Prompt	Purpose
introduce	Explains CFFBRW MCP — run this first
compile	Guides the full compile → validate → deploy → run flow

Example: Agent Flow

User: "Automate a weekly lead report every Monday"

1. Agent reads MCP resources (schema, step types)
2. Agent generates execution plan JSON
3. Agent calls validate_plan → resolves connector intents + validates
4. Agent calls deploy_workflow
5. Agent calls schedule_workflow with cron "0 9 * * MON"
6. Done — runs every Monday, no AI tokens

When to Use CFFBRW

Use CFFBRW when you need:

• Repeatable multi-step automation on Cloudflare edge
• Human approval gates that pause for days at zero cost
• Self-healing execution (AI fixes runtime failures automatically)
• Cron or webhook-triggered workflows
• Cost efficiency: compile once, run forever (~$0.00005/run)

Don't use CFFBRW when:

• The task needs fresh reasoning every time (use an agent loop)
• You want drag-and-drop (use Zapier or Make)
• It's a one-off that won't repeat

Cloudflare Primitives

CFFBRW wraps Workers, Durable Objects, D1, KV, R2, and AgentWorkflow — so you don't manage them directly.

11 Step Types

http_request | ai_call | transform | conditional | loop | wait | human_approval | code | mcp_call | connector | sub_workflow

Connector Catalog

Google Drive, Sheets, Calendar, Gmail, Slack, Discord, Notion, SendGrid, Resend, Webhook, Custom HTTP.

Pricing

Plan	Credits/mo	Workflows	MCP Servers
Free	100	5	2
Pro	1,000	50	10
Team	5,000	Unlimited	25

Compile = 10 credits. Run per step = 1 credit. AI recovery = 5 credits. validate_plan = free.

Links

• Homepage: cffbrw.com
• Dashboard: cffbrw.com/workflows
• Docs: cffbrw.com/docs/agent-guide
• API Reference: cffbrw.com/docs/api-reference
• Full LLM Reference: cffbrw.com/llms-full.txt
• API Base URL: https://api.cffbrw.com
• MCP Endpoint: https://api.cffbrw.com/mcp

License

MIT