Cloudbase Agent Python
Build production-ready AI agent backends using the CloudBase Agent Python SDK, create...
Install
npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill cloudbase-agent-python -g -a claude-code -y- Repository
- TencentCloudBase/CloudBase-AI-Toolkit1.2k
- Category
- Design
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 2,684 tokens
- Runs scripts
- No, instructions only
What it does
Build production-ready AI agent backends using the CloudBase Agent Python SDK, create agents with LangGraph/CrewAI/LlamaIndex, serve them via FastAPI with AG-UI protocol streaming + OpenAI-compatible endpoints, add tools (bash, filesystem, MCP, code execution), memory (in-memory, TDAI, MySQL, MongoDB), observability (OpenTelemetry/Langfuse), and middleware (auth, logging). Use this skill when the user wants to create an AI agent server, build a chatbot backend, set up human-in-the-loop workflows, integrate MCP tools, add agent observability, or deploy an agent API, even if they don't explicitly mention 'CloudBase Agent.
CloudBase Agent Python SDK
Build production-ready AI agent backends with multi-framework support, streaming protocol, rich tools, persistent memory, and full observability.
Note: This skill is for Python 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, CrewAI, or LlamaIndex frameworks
- Create custom agent adapters implementing the AbstractAgent interface
- Understand AG-UI protocol events and message streaming
- Build production-ready agent servers with FastAPI
Do NOT use for:
- Simple AI model calling without agent capabilities (use
ai-model-*skills) - CloudBase cloud functions (use
cloud-functionsskill) - CloudRun backend services without agent features (use
cloudrun-developmentskill) - TypeScript/JavaScript agent projects (use
cloudbase-agentskill, refer to thets/sub-directory)
How to use this skill (for a coding agent)
-
Choose the right adapter
- Use LangGraph adapter for stateful, graph-based workflows
- Use CrewAI adapter for multi-agent collaboration patterns
- Build custom adapter for specialized agent logic
-
Write agent code, follow the adapter-specific doc from the Routing table
-
Deploy the agent server, follow the blocking deployment pipeline in agent-deployment
Routing (Execution Order)
⚠️ Deployment is a BLOCKING 4-step pipeline. Steps marked ✅ BLOCKING must be completed AND verified before proceeding to the next step. Do NOT call
manageAgentuntil all blocking steps pass.
