agents-sdk
Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.
DeepseekModel
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Standard format with system_prompt and model_config, ready for any agent framework
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name agents-sdk description Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Cloudflare Agents SDK STOP. Your knowledge of the Agents SDK may be outdated. Prefer retrieval over pre-training for any Agents SDK task. Documentation Fetch current docs from https://github.com/cloudflare/agents/tree/main/docs before implementing. Topic Doc Use for Getting started docs/getting-started.md First agent, project setup State docs/state.md setState , validateStateChange , persistence Routing docs/routing.md URL patterns, routeAgentRequest , basePath Callable methods docs/callable-methods.md @callable , RPC, streaming, timeouts Scheduling docs/scheduling.md schedule() , scheduleEvery() , cron Workflows docs/workflows.md AgentWorkflow , durable multi-step tasks HTTP/WebSockets docs/http-websockets.md Lifecycle hooks, hibernation Email docs/email.md Email routing, secure reply resolver MCP client docs/mcp-client.md Connecting to MCP servers MCP server docs/mcp-servers.md Building MCP servers with McpAgent Client SDK docs/client-sdk.md useAgent , useAgentChat , React hooks Human-in-the-loop docs/human-in-the-loop.md Approval flows, pausing workflows Resumable streaming docs/resumable-streaming.md Stream recovery on disconnect Cloudflare docs: https://developers.cloudflare.com/agents/ Capabilities The Agents SDK provides: Persistent state - SQLite-backed, auto-synced to clients Callable RPC - @callable() methods invoked over WebSocket Scheduling - One-time, recurring ( scheduleEvery ), and cron tasks Workflows - Durable multi-step background processing via AgentWorkflow MCP integration - Connect to MCP servers or build your own with McpAgent Email handling - Receive and reply to emails with secure routing Streaming chat - AIChatAgent with resumable streams React hooks - useAgent , useAgentChat for client apps FIRST: Verify Installation npm ls agents # Should show agents package If not installed: npm install agents Wrangler Configuration { "durable_objects" : { "bindings" : [ { "name" : "MyAgent" , "class_name" : "MyAgent" } ] , } , "migrations" : [ { "tag" : "v1" , "new_sqlite_classes" : [ "MyAgent" ] } ] , } Agent Class import { Agent , routeAgentRequest, callable } from "agents" type State = { count : number } export class Counter extends Agent < Env , State > { initialState = { count : 0 } // Validation hook - runs before state persists (sync, throwing rejects the update) validateStateChange ( nextState : State , source : Connection | "server" ) { if (nextState. count < 0 ) throw new Error ( "Count cannot be negative" ) } // Notification hook - runs after state persists (async, non-blocking) onStateUpdate ( state : State , source : Connection | "server" ) { console . log ( "State updated:" , state) } @callable () increment ( ) { this . setState ({ count : this . state . count + 1 }) return this . state . count } } export default { fetch : ( req, env ) => routeAgentRequest (req, env) ?? new Response ( "Not found" , { status : 404 }), } Routing Requests route to /agents/{agent-name}/{instance-name} : Class URL Counter /agents/counter/user-123 ChatRoom /agents/chat-room/lobby Client: useAgent({ agent: "Counter", name: "user-123" }) Core APIs Task API Read state this.state.count Write state this.setState({ count: 1 }) SQL query this.sql`SELECT * FROM users WHERE id = ${id}` Schedule (delay) await this.schedule(60, "task", payload) Schedule (cron) await this.schedule("0 * * * *", "task", payload) Schedule (interval) await this.scheduleEvery(30, "poll") RPC method @callable() myMethod() { ... } Streaming RPC @callable({ streaming: true }) stream(res) { ... } Start workflow await this.runWorkflow("ProcessingWorkflow", params) React Client import { useAgent } from "agents/react" function App ( ) { const [state, setLocalState] = useState ({ count : 0 }) const agent = useAgent ({ agent : "Counter" , name : "my-instance" , onStateUpdate : ( newState ) => setLocalState (newState), onIdentity : ( name, agentType ) => console . log ( `Connected to ${name} ` ), }) return < button onClick = {() => agent.setState({ count: state.count + 1 })}>Count: {state.count} </ button > } References references/workflows.md - Durable Workflows integration references/callable.md - RPC methods, streaming, timeouts references/state-scheduling.md - State persistence, scheduling references/streaming-chat.md - AIChatAgent, resumable streams references/mcp.md - MCP server integration references/email.md - Email routing and handling references/codemode.md - Code Mode (experimental)
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The downloaded .skill package contains the following fields.
| Field | Description |
|---|---|
| format | Format tag (skill/v1) |
| skill_id | Unique skill ID |
| name | Skill name |
| version | Version |
| description | Description |
| category | Categories (array) |
| trigger_words | Trigger words |
| tags | Tags |
| source | Source |
| source_url | Source URL (this page) |
| exported_at | Exported at (set per download) |
| system_prompt | System prompt body |
| model_config | Model config: provider / model / temperature / max_tokens / top_p |
| examples | Examples |
| install_guide | Import guide for Coze / Dify / Claude / custom frameworks |
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