building-ai-agent-on-cloudflare
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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Install
Works with every agent the skills CLI supports.
npx skills add https://developers.cloudflare.com --skill building-ai-agent-on-cloudflare- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads building-ai-agent-on-cloudflare automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Building Cloudflare Agents
Your knowledge of the Agents SDK may be outdated. Prefer retrieval over pre-training for any agent-building task.
Retrieval Sources
| Source | How to retrieve | Use for |
|---|---|---|
| Agents SDK docs | https://github.com/cloudflare/agents/tree/main/docs | SDK API, state, routing, scheduling |
| Cloudflare Agents docs | https://developers.cloudflare.com/agents/ | Platform integration, deployment |
| Workers docs | Search tool or https://developers.cloudflare.com/workers/ | Runtime APIs, bindings, config |
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,
}));
}
}
Entry Point Configuration
// src/index.ts
import { routeAgentRequest } from "agents";
import { MyAgent } from "./agent";
export default {
async fetch(request: Request, env: Env) {
// routeAgentRequest handles routing to /agents/:class/:name
return (
(await routeAgentRequest(request, env)) ||
new Response("Not found", { status: 404 })
);
},
};
export { MyAgent };
Clients connect via: wss://my-agent.workers.dev/agents/MyAgent/session-id
Wrangler Configuration
{
"name": "my-agent",
"main": "src/index.ts",
"compatibility_date": "2024-12-01",
"ai": { "binding": "AI" },
"durable_objects": {
"bindings": [{ "name": "MyAgent", "class_name": "MyAgent" }]
},
"migrations": [{ "tag": "v1", "new_sqlite_classes": ["MyAgent"] }]
}
State Management
Reading State
// Current state is always available
const currentMessages = this.state.messages;
const userPrefs = this.state.preferences;
Updating State
// setState persists AND syncs to all connected clients
this.setState({
...this.state,
messages: [...this.state.messages, newMessage],
});
// Partial updates work too
this.setState({
preferences: { ...this.state.preferences, theme: "dark" },
});
SQL Storage
For complex queries, use the embedded SQLite database:
// Create tables
await this.sql`
CREATE TABLE IF NOT EXISTS documents (
id INTEGER PRIMARY KEY AUTOINCREMENT,
title TEXT NOT NULL,
content TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
)
`;
// Insert
await this.sql`
INSERT INTO documents (title, content)
VALUES (${title}, ${content})
`;
// Query
const docs = await this.sql`
SELECT * FROM documents WHERE title LIKE ${`%${search}%`}
`;
Scheduled Tasks
Agents can schedule future work:
async onMessage(connection: Connection, message: string) {
const data = JSON.parse(message);
if (data.type === "schedule_reminder") {
// Schedule task for 1 hour from now
const { id } = await this.schedule(3600, "sendReminder", {
message: data.reminderText,
userId: data.userId,
});
connection.send(JSON.stringify({ type: "scheduled", taskId: id }));
}
}
// Called when scheduled task fires
async sendReminder(data: { message: string; userId: string }) {
// Send notification, email, etc.
console.log(`Reminder for ${data.userId}: ${data.message}`);
// Can also update state
this.setState({
...this.state,
lastReminder: new Date().toISOString(),
});
}
Schedule Options
// Delay in seconds
await this.schedule(60, "taskMethod", { data });
// Specific date
await this.schedule(new Date("2025-01-01T00:00:00Z"), "taskMethod", { data });
// Cron expression (recurring)
await this.schedule("0 9 * * *", "dailyTask", {}); // 9 AM daily
await this.schedule("*/5 * * * *", "everyFiveMinutes", {}); // Every 5 min
// Manage schedules
const schedules = await this.getSchedules();
await this.cancelSchedule(taskId);
Chat Agent (AI-Powered)
For chat-focused agents, extend AIChatAgent:
import { AIChatAgent } from "@cloudflare/ai-chat";
export class ChatBot extends AIChatAgent<Env> {
// Called for each user message
async onChatMessage(message: string) {
const response = await this.env.AI.run("@cf/meta/llama-3-8b-instruct", {
messages: [
{ role: "system", content: "You are a helpful assistant." },
...this.messages, // Automatic history management
{ role: "user", content: message },
],
stream: true,
});
// Stream response back to client
return response;
}
}
Features included:
- Automatic message history
- Resumable streaming (survives disconnects)
- Built-in
saveMessages()for persistence
Client Integration
React Hook
import { useAgent } from "agents/react";
function Chat() {
const { state, send, connected } = useAgent({
agent: "my-agent",
name: userId, // Agent instance ID
});
const sendMessage = (text: string) => {
send(JSON.stringify({ type: "chat", content: text }));
};
return (
<div>
{state.messages.map((msg, i) => (
<div key={i}>{msg.role}: {msg.content}</div>
))}
<input onKeyDown={(e) => e.key === "Enter" && sendMessage(e.target.value)} />
</div>
);
}
Vanilla JavaScript
const ws = new WebSocket("wss://my-agent.workers.dev/agents/MyAgent/user123");
ws.onopen = () => {
console.log("Connected to agent");
};
ws.onmessage = (event) => {
const data = JSON.parse(event.data);
console.log("Received:", data);
};
ws.send(JSON.stringify({ type: "chat", content: "Hello!" }));
Common Patterns
See references/agent-patterns.md for:
- Tool calling and function execution
- Multi-agent orchestration
- RAG (Retrieval Augmented Generation)
- Human-in-the-loop workflows
Deployment
# Deploy
npx wrangler deploy
# View logs
wrangler tail
# Test endpoint
curl https://my-agent.workers.dev/agents/MyAgent/test-user
Troubleshooting
See references/troubleshooting.md for common issues.
References
- references/examples.md — Official templates and production examples
- references/agent-patterns.md — Advanced patterns
- references/state-patterns.md — State management strategies
- references/troubleshooting.md — Error solutions
FAQ
What does the building-ai-agent-on-cloudflare skill do?
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
How do I install building-ai-agent-on-cloudflare?
Run npx skills add https://developers.cloudflare.com --skill building-ai-agent-on-cloudflare in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/building-ai-agent-on-cloudflare/ (personal) or .claude/skills/building-ai-agent-on-cloudflare/ (project).
Which AI agents can use building-ai-agent-on-cloudflare?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is building-ai-agent-on-cloudflare safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains building-ai-agent-on-cloudflare?
It is published by developers.cloudflare.com in developers.cloudflare.com. It has 185 recorded installs.
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