building-ai-agent-on-cloudflare

building-ai-agent-on-cloudflare is a skill for Claude Code, Codex from GrayCodeAI/starling. It costs 37 tokens per session (2,014 once invoked), scanned A, original, MIT.

A workflow for building stateful AI agents on Cloudflare using the Agents SDK. These agents can remember state, communicate through WebSockets or HTTP, run scheduled work, and use tools.

In plain words
What is it for?
Use it to build AI agents or chatbots with persistent sessions, real-time communication, scheduled tasks, and tool integrations. It assumes a Cloudflare account, a JavaScript runtime, and the Wrangler command-line tool.
Why use it?
It provides a structured way to create agents that keep state between interactions and run on Cloudflare's edge infrastructure. It also covers the setup needed to start a working agent project.

Skill for Claude CodeCodex

Part of the starling plugin — 54 skills shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/graycodeai/starling/building-ai-agent-on-cloudflare
Any agent
npx skills add GrayCodeAI/starling --skill building-ai-agent-on-cloudflare
Clone the repo
git clone --depth 1 https://github.com/GrayCodeAI/starling

Made for: Claude Code, Codex.

Or install starling, the plugin that ships this one along with the rest of its 54 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for building-ai-agent-on-cloudflare

README.md
[![agentmods](https://agentmods.dev/badge/skills/graycodeai/starling/building-ai-agent-on-cloudflare.svg)](https://agentmods.dev/skills/graycodeai/starling/building-ai-agent-on-cloudflare)
Your own site
<a href="https://agentmods.dev/skills/graycodeai/starling/building-ai-agent-on-cloudflare"><img src="https://agentmods.dev/badge/skills/graycodeai/starling/building-ai-agent-on-cloudflare.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,014 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.02014
Opus 5 $0.00018 $0.01007
Sonnet 5 $0.00007 $0.00403
Haiku 4.5 $0.00004 $0.00201

Measured 5d ago against content hash 270ea8079963, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

building-ai-agent-on-cloudflare scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

async fetch(request: Request, env: Env) {
categories/ai-ml/building-ai-agent-on-cloudflare/SKILL.md · 364 lines

How it starts

The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Building Cloudflare Agents

Creates AI-powered agents using Cloudflare's Agents SDK with persistent state, real-time communication, and tool integration.

When to Use

  • User wants to build an AI agent or chatbot
  • User needs stateful, real-time AI interactions
  • User asks about the Cloudflare Agents SDK
  • User wants scheduled tasks or background AI work
  • User needs WebSocket-based AI communication

Prerequisites

  • Cloudflare account with Workers enabled
  • Node.js 18+ and npm/pnpm/yarn
  • Wrangler CLI (npm install -g wrangler)

Quick Start

npm create cloudflare@latest -- my-agent --template=cloudflare/agents-starter
cd my-agent
npm start

Agent runs at http://localhost:8787

Core Concepts

What is an Agent?

An Agent is a stateful, persistent AI service that:

  • Maintains state across requests and reconnections
  • Communicates via WebSockets or HTTP
  • Runs on Cloudflare's edge via Durable Objects
  • Can schedule tasks and call tools
  • Scales horizontally (each user/session gets own instance)

Agent Lifecycle

Client connects -> Agent.onConnect() -> Agent processes messages
                                     -> Agent.onMessage()
                                     -> Agent.setState() (persists + syncs)
Client disconnects -> State persists -> Client reconnects -> State restored

Basic Agent Structure

import { Agent, Connection } from "agents";

interface Env {
  AI: Ai;  // Workers AI binding
}

interface State {
  messages: Array<{ role: string; content: string }>;
  preferences: Record<string, string>;
}

export class MyAgent extends Agent<Env, State> {
  // Initial state for new instances
  initialState: State = {
    messages: [],
    preferences: {},
  };

  // Called when agent starts or resumes
  async onStart() {
    console.log("Agent started with state:", this.state);
  }

  // Handle WebSocket connections
  async onConnect(connection: Connection) {
    connection.send(JSON.stringify({
      type: "welcome",
      history: this.state.messages,
    }));
  }

  // Handle incoming messages
  async onMessage(connection: Connection, message: string) {
    const data = JSON.parse(message);

    if (data.type === "chat") {
      await this.handleChat(connection, data.content);
    }
  }

  // Handle disconnections
  async onClose(connection: Connection) {
    console.log("Client disconnected");
  }

  // React to state changes
  onStateUpdate(state: State, source: string) {
    console.log("State updated by:", source);
  }

  private async handleChat(connection: Connection, userMessage: string) {
    // Add user message to history
    const messages = [
      ...this.state.messages,
      { role: "user", content: userMessage },
    ];

    // Call AI
    const response = await this.env.AI.run("@cf/meta/llama-3-8b-instruct", {
      messages,
    });

    // Update state (persists and syncs to all clients)
    this.setState({
      ...this.state,
      messages: [
        ...messages,
        { role: "assistant", content: response.response },
      ],
    });

    // Send response
    connection.send(JSON.stringify({
      type: "response",
      content: response.response,
    }));
  }
}

Read the full file on GitHub · 364 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 364 lines · 37 tokens per session scan A 270ea8079963

Subscribe to this mod's changes

building-ai-agent-on-cloudflare is a skill published in the GitHub repository GrayCodeAI/starling (2 stars, last pushed 6d ago), licensed MIT. It adds 37 tokens to every session and 2,014 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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