cloudflare

✓Verified·Scanned 2/18/2026

This skill is a comprehensive Cloudflare platform reference for Workers, AI, storage, networking, and tooling. It includes runnable CLI commands (e.g., npx wrangler deploy, curl), instructs storing/using secrets (CLOUDFLARE_API_TOKEN, OPENAI_API_KEY), and exposes API endpoints such as https://api.cloudflare.com/....

by dmmulroy·v97a85fd·1.3 MB·257 installs

Scanned from main at 97a85fd · Transparency log ↗

$ vett add dmmulroy/cloudflare-skill/cloudflare

Cloudflare Agents SDK

Cloudflare Agents SDK enables building AI-powered agents on Durable Objects with state, WebSockets, SQL, scheduling, and AI integration.

Core Value

Build stateful, globally distributed AI agents with persistent memory, real-time connections, scheduled tasks, and async workflows.

When to Use

Persistent state + memory required
Real-time WebSocket connections
Long-running workflows (minutes/hours)
Chat interfaces with AI models
Scheduled/recurring tasks with state
DB queries with agent state

What Type of Agent?

Use Case	Class	Key Features
AI chat interface	`AIChatAgent`	Auto-streaming, tools, message history, resumable
MCP tool provider	`Agent` + MCP	Expose tools to AI systems
Custom logic/routing	`Agent`	Full control, WebSockets, email, SQL
Real-time collaboration	`Agent`	WebSocket state, broadcasts
Email processing	`Agent`	`onEmail()` handler

Quick Start

AI Chat Agent:

import { AIChatAgent } from "agents";
import { openai } from "@ai-sdk/openai";

export class ChatAgent extends AIChatAgent<Env> {
  async onChatMessage(onFinish) {
    return this.streamText({
      model: openai("gpt-4"),
      messages: this.messages,
      onFinish,
    });
  }
}

Base Agent:

import { Agent } from "agents";

export class MyAgent extends Agent<Env> {
  onStart() {
    this.sql`CREATE TABLE IF NOT EXISTS users (id TEXT PRIMARY KEY)`;
  }
  
  async onRequest(request: Request) {
    return Response.json({ state: this.state });
  }
}

Reading Order

Task	Files to Read
Quick start	README only
Build chat agent	README → api.md (AIChatAgent) → patterns.md
Setup project	README → configuration.md
Add React frontend	README → api.md (Client Hooks) → patterns.md
Build MCP server	api.md (MCP) → patterns.md
Background tasks	api.md (Scheduling, Task Queue) → patterns.md
Debug issues	gotchas.md

Package Entry Points

Import	Purpose
`agents`	Server-side Agent classes, lifecycle
`agents/react`	`useAgent()` hook for WebSocket connections
`agents/ai-react`	`useAgentChat()` hook for AI chat UIs

In This Reference

configuration.md - SDK setup, wrangler config, routing
api.md - Agent classes, lifecycle, client hooks
patterns.md - Common workflows, best practices
gotchas.md - Common issues, limits