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cloudbase-agent

Deploy AI agents as HTTP services with AG-UI protocol support.

Updated Apr 13, 2026
Search Tags:#typescript#python#agent#protocol#deploy#cloudbase#scalable
One-click install
npx skills add https://github.com/lance-donif/xionghaizi --skill cloudbase-agent-lance-donif
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cloudbase-agent
Source: https://github.com/lance-donif/xionghaizi/tree/main/.trae/skills/cloudbase-agent
Command: npx skills add https://github.com/lance-donif/xionghaizi --skill cloudbase-agent-lance-donif

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @cloudbase/agent-server, @cloudbase/agent-adapter-langgraph, @langchain/langgraph, @langchain/openai, and includes references (resource) and scripts (resource) and assets (resource) components.

What problem does it solve?

This Skill enables building and deploying AI agents using CloudBase Agent SDKs in TypeScript and Python, simplifying the process of creating scalable, protocol-compatible AI services.

Core Features & Use Cases

  • Agent Deployment and Management: Enables deploying AI agents as HTTP services supporting the AG-UI protocol with both TypeScript and Python SDKs.
  • Protocol Compatibility: Implements streaming communication, OpenAI-compatible endpoints, and message handling for frontend integrations and UI clients.
  • Custom Adapter Development: Provides detailed guidance on creating custom protocol adapters for diverse frameworks and use cases.
  • Use Case: Build a web-based AI assistant or chatbot backend that can handle real-time conversations, integrate tools, and support multi-framework extension.

Quick Start

Create an agent with LangGraph and deploy it as an HTTP server using FastAPI, then connect via frontend clients to provide seamless AI interactions.

Frequently Asked Questions about cloudbase-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy a LangGraph agent as an HTTP server with AG-UI protocol support?▼

Deploy a LangGraph agent as an HTTP server with AG-UI protocol support by using CloudBase Agent SDKs with FastAPI to create scalable AI services handling real-time streaming and custom protocol messaging.

What is the AG-UI protocol for building scalable AI assistants?▼

The AG-UI protocol for scalable AI assistants enables streaming communication, OpenAI-compatible endpoints, and message handling for frontend integrations, allowing web-based chatbots to process real-time conversations and backend integrations seamlessly.

Can I use TypeScript and Python to build AI chatbot backends with CloudBase?▼

Yes, you can use TypeScript and Python to build AI chatbot backends with CloudBase by leveraging dedicated SDKs to implement agent deployment, protocol compatibility, and custom adapter development for frontend UI clients.

Does the CloudBase Agent SDK support OpenAI-compatible endpoints for frontend integrations?▼

Yes, the CloudBase Agent SDK supports OpenAI-compatible endpoints for frontend integrations, implementing streaming communication and message handling to connect AI agents directly with UI clients.

What is the best way to create custom protocol adapters for AI agents?▼

The best way to create custom protocol adapters for AI agents is using the CloudBase SDKs, which provide detailed guidance on building adapters for diverse frameworks to handle specific multi-framework extension requirements.

When do I need custom protocol handling for AI service deployment?▼

You need custom protocol handling for AI service deployment when building web-based AI assistants or chatbot backends that require real-time streaming, tool integration, and multi-framework extension support via the AG-UI protocol.

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