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name: cloudbase-agent description: "Build and deploy AI agents with Cloudbase Agent (TypeScript), a TypeScript SDK implementing the AG-UI protocol. Use when: (1) deploying agent servers with @cloudbase/agent-server, (2) using LangGraph adapter with ClientStateAnnotation, (3) using LangChain adapter with clientTools(), (4) building custom adapters that implement AbstractAgent, (5) understanding AG-UI protocol events, (6) building web UI clients with @ag-ui/client, (7) building WeChat Mini Program UIs with @cloudbase/agent-ui-miniprogram." version: 2.34.8 alwaysApply: true

Cloudbase Agent (TypeScript)

TypeScript SDK for deploying AI agents as HTTP services using the AG-UI protocol.

Note: This skill is for TypeScript/JavaScript projects only.

When to use this skill

Use this skill for AI agent development when you need to:

• Deploy AI agents as HTTP services with AG-UI protocol support
• Build agent backends using LangGraph or LangChain frameworks
• Create custom agent adapters implementing the AbstractAgent interface
• Understand AG-UI protocol events and message streaming
• Build web UI clients that connect to AG-UI compatible agents
• Build WeChat Mini Program UIs for AI agent interactions

Do NOT use for:

• Simple AI model calling without agent capabilities (use ai-model-* skills)
• CloudBase cloud functions (use cloud-functions skill)
• CloudRun backend services without agent features (use cloudrun-development skill)

How to use this skill (for a coding agent)

1. Choose the right adapter

   • Use LangGraph adapter for stateful, graph-based workflows
   • Use LangChain adapter for chain-based agent patterns
   • Build custom adapter for specialized agent logic

2. Deploy the agent server

   • Use @cloudbase/agent-server to expose HTTP endpoints
   • Configure CORS, logging, and observability as needed
   • Prefer deploying to CloudBase using manageAgent MCP tool (see agent-deployment)
   • Before deploy, read Dependency Alignment Policy in agent-deployment to avoid cloud build dependency errors

3. Build the UI client

   • Use @ag-ui/client for web applications
   • Use @cloudbase/agent-ui-miniprogram for WeChat Mini Programs
   • Connect to the agent server's /send-message or /agui endpoints

4. Follow the routing table below to find detailed documentation for each task

Routing

| Task | Read | |------|------| | Deploy agent to CloudBase (read this first) | agent-deployment | | Deploy agent server (@cloudbase/agent-server) | server-quickstart | | Use LangGraph adapter | adapter-langgraph | | Use LangChain adapter | adapter-langchain | | Build custom adapter | adapter-development | | Understand AG-UI protocol | agui-protocol | | Build UI client (Web or Mini Program) | ui-clients | | Deep-dive @cloudbase/agent-ui-miniprogram | ui-miniprogram |

Quick Start

Prerequisites: Node.js >= 20 is required.

1. Install dependencies:

npm install @cloudbase/agent-server@latest @cloudbase/agent-adapter-langgraph@latest

Critical: Always use @latest for all @cloudbase/agent-* packages. For dependency version rules, see Dependency Alignment Policy in agent-deployment.md.

2. Create and run your agent:

import { run } from "@cloudbase/agent-server";
import { LanggraphAgent } from "@cloudbase/agent-adapter-langgraph";

run({
  createAgent: () => ({ agent: new LanggraphAgent({ workflow }) }),
  port: 9000,
});