cloudbase-agent-python

TencentCloudBase1.2kstars

DatabasesAnalytics MonitoringAutonomous Agents

1---2name: cloudbase-agent-python3description: Build production-ready AI agent backends using the CloudBase Agent Python SDK — create agents with…4---56# config/.claude/skills/cloudbase-agent/py/skill.md

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SKILL.md

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1Install this skill: https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/tree/HEAD/config/.claude/skills/cloudbase-agent/py

Download skill config/.claude/skills/cloudbase-agent/py/skill.md on GitHub

config/.claude/skills/cloudbase-agent/py/skill.mdMarkdown · UTF-8

Skill facts

Agent skill

File: config/.claude/skills/cloudbase-agent/py/skill.md
Publisher: TencentCloudBase
Hosting

Overview

About cloudbase-agent-python

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.'

FAQ

Questions

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-functions skill)

CloudRun backend services without agent features (use cloudrun-development skill)

TypeScript/JavaScript agent projects (use cloudbase-agent skill, refer to the ts/ 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 manageAgent until all blocking steps pass.

Step	Task	Document	Blocking?
0	Choose adapter & write agent code	See "Adapter Selection" below	—
1	Ensure Python 3.10	agent-deployment § Step 1	✅ BLOCKING
2	Build env/ (one-shot)	agent-deployment § Step 2	✅ BLOCKING
3	Verify env/ integrity	agent-deployment § Step 3	✅ BLOCKING
4	Deploy with manageAgent	agent-deployment § Step 4	—

Framework	Read	Install
LangGraph (stateful graphs)	adapter-langgraph	`cloudbase-agent-langgraph`
CrewAI (multi-agent crews)	adapter-development	`cloudbase-agent-crewai`
Coze platform	adapter-coze	`cloudbase-agent-coze`
Custom / raw FastAPI	server-quickstart + adapter-development	`cloudbase-agent-server`

Task	Read
Server setup, middleware, multi-agent, CORS	server-quickstart
Authentication and user context	authentication

User Need	Reference	What It Covers
Deploying agent to CloudBase	Read agent-deployment	manageAgent MCP tool (MUST USE), 4-step blocking pipeline, Python 3.10, env/ build, verification
Server setup, deployment, middleware, multi-agent, CORS	Read `references/server.md`	AgentServiceApp 3 deployment methods, middleware (generator/yield/onion model), multi-agent server, Agent Creator pattern, health checks
LangGraph agent, callbacks, tool proxy, HITL, checkpoints	Read adapter-langgraph	LangGraphAgent constructor, AgentCallback protocol, ToolProxy, human-in-the-loop with interrupt(), TDAICheckpointSaver, client-defined tools
Tools: bash, filesystem, code execution, MCP, custom tools	Read `references/tools.md`	create_bash_tool, 8 file tools, code executors, MCPToolkit/CloudBaseMCPServer, @tool decorator, BaseTool, framework adapters
Memory, persistence, short/long-term, MySQL, MongoDB	Read `references/storage.md`	InMemoryMemory, TDAIMemory, MySQLMemory, MongoDBMemory, TDAILongTermMemory, Mem0LongTermMemory, LangGraph checkpoint
Tracing, monitoring, Langfuse, OpenTelemetry	Read `references/observability.md`	ConsoleTraceConfig, OTLPTraceConfig, setup_observability, env vars, manual observation spans
Common patterns, JWT auth, MCP integration, production	Read `references/recipes.md`	JWT middleware, MCP + LangGraph, production deployment, adding tools to agents, client-defined tools

Variable	Purpose
`OPENAI_API_KEY`	OpenAI API key
`AUTO_TRACES_STDOUT`	Enable console tracing (`true`)
`LANGFUSE_PUBLIC_KEY` / `LANGFUSE_SECRET_KEY`	Langfuse keys
`TDAI_ENDPOINT` / `TDAI_API_KEY`	TDAI memory/checkpoint endpoint
`SCF_RUNTIME_PORT`	CloudBase runtime port (set automatically during deployment)

cloudbase-agent-python

Install

Skill facts

About cloudbase-agent-python

Questions

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SKILL.md