Cloudbase Agent Python

What it does

When your agent uses it

• The user wants to create an AI agent server
• Build a chatbot backend
• Set up human-in-the-loop workflows
• Integrate MCP tools

Example prompts

• “t explicitly mention”
• “/cloudbase-agent-python”

Requirements

• Python 3
• A credential in OPENAI_API_KEY
• A credential in LANGFUSE_PUBLIC_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

1. 1Choose the right adapter
2. 2Write agent code — follow the adapter-specific doc from the Routing table
3. 3Deploy the agent server — follow the blocking deployment pipeline in agent-deployment

What it can do on your machine

Read from SKILL.md and the folder at commit ea2c202. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • pip

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • OPENAI_API_KEY
  • LANGFUSE_PUBLIC_KEY
  • LANGFUSE_SECRET_KEY
  • TDAI_API_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cloudbase Agent Python loads about 2.9k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 163 tokens; SKILL.md has 678 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~163

When it runs · the whole SKILL.md, loaded when a task matches

~2.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~11k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NoteMentions a .env fileSKILL.md:225

  ├── .env                            # OPENAI_API_KEY, etc.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TencentCloudBase/CloudBase-AI-Toolkit at commit ea2c202, republished under its MIT licence (© TencentCloudBase). 678 words, ~2,864 tokens.

name

cloudbase-agent-python

description

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.'

version

2.34.8

alwaysApply

true

# Option A: LangGraph-based agent
pip install cloudbase-agent-langgraph

# Option B: CrewAI-based agent
pip install cloudbase-agent-crewai

# Option C: Custom / minimal
pip install cloudbase-agent-server

# server.py — this pattern works with ANY adapter
import os
from dotenv import load_dotenv
load_dotenv()

from cloudbase_agent.server import AgentServiceApp, AgentCreatorResult

# Import your agent (framework-specific, see adapter docs)
# from agents.chat.agent import create_my_agent

def create_agent() -> AgentCreatorResult:
    agent = create_my_agent()  # Your agent factory
    return {"agent": agent}

app = AgentServiceApp()
app.set_cors_config(allow_origins=["*"])

if __name__ == "__main__":
    port = int(os.environ.get("SCF_RUNTIME_PORT", "9000"))
    app.run(create_agent, port=port, host="0.0.0.0")

Client (React / MiniProgram / curl)
   │  HTTP POST + SSE streaming
   ▼
┌─────────────────────────────────────────────┐
│  AgentServiceApp (FastAPI)                   │
│  ├─ /send-message      ← AG-UI SSE         │
│  ├─ /chat/completions  ← OpenAI-compat      │
│  └─ Middleware chain (onion model)           │
├─────────────────────────────────────────────┤
│  Agent Layer                                 │
│  ├─ LangGraphAgent  ├─ CrewAIAgent          │
│  ├─ LlamaIndexAgent ├─ CozeAgent/DifyAgent  │
│  └─ BaseAgent (extend for custom)           │
├──────────────────┬──────────────────────────┤
│  Tools           │  Storage                  │
│  Bash/FS/Code/MCP│  Memory + LongTermMemory  │
├─────────────────────────────────────────────┤
│  Observability (OpenTelemetry + Langfuse)    │
└─────────────────────────────────────────────┘

# Core + Server + LangGraph (most common)
pip install cloudbase-agent-langgraph

# Individual packages
pip install cloudbase-agent-core        # Core framework
pip install cloudbase-agent-server      # FastAPI server
pip install cloudbase-agent-langgraph   # LangGraph integration
pip install cloudbase-agent-tools       # Tool system
pip install cloudbase-agent-storage     # Memory/Storage
pip install cloudbase-agent-observability  # OpenTelemetry/Langfuse
pip install cloudbase-agent-coze        # Coze platform
pip install cloudbase-agent-crewai      # CrewAI integration

# After installing cloudbase-agent-langgraph, import from cloudbase_agent
from cloudbase_agent.langgraph import LangGraphAgent
from cloudbase_agent.server import AgentServiceApp
from cloudbase_agent.tools import create_bash_tool

# Server
from cloudbase_agent.server import AgentServiceApp, AgentCreatorResult
from cloudbase_agent.server import create_send_message_adapter, create_openai_adapter
from cloudbase_agent.server import RunAgentInput, OpenAIChatCompletionRequest

# Agents
from cloudbase_agent.langgraph import LangGraphAgent
from cloudbase_agent.crewai import CrewAIAgent

# Tools
from cloudbase_agent.tools import create_bash_tool, create_read_tool, create_write_tool
from cloudbase_agent.tools import MCPToolkit, CloudBaseMCPServer, CloudBaseTool
from cloudbase_agent.tools import tool, BaseTool  # custom tools

# Storage
from cloudbase_agent.storage import InMemoryMemory, TDAIMemory
from cloudbase_agent.storage import TDAILongTermMemory, Mem0LongTermMemory
from cloudbase_agent.langgraph import TDAICheckpointSaver, TDAIStore

# Observability
from cloudbase_agent.observability import ConsoleTraceConfig, OTLPTraceConfig, setup_observability

# Schemas
from cloudbase_agent.schemas import Message, MessageRole, StreamEvent, EventType

my-agent-project/
├── agents/
│   ├── agentic_chat/agent.py      # build_workflow() → agent instance
│   ├── human_in_the_loop/agent.py
│   └── __init__.py
├── server.py                       # Main entry: AgentServiceApp().run(...)
├── scf_bootstrap                   # CloudBase startup script (required for deployment)
├── .env                            # OPENAI_API_KEY, etc.
└── requirements.txt

© TencentCloudBase, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references) in config/source/skills/cloudbase-agent/py of TencentCloudBase/CloudBase-AI-Toolkit.

• SKILL.md
• adapter-coze.md
• adapter-development.md
• adapter-langgraph.md
• agent-deployment.md
• authentication.md
• references/observability.md
• references/recipes.md
• references/server.md
• references/storage.md
• references/tools.md
• server-quickstart.md

Open the folder on GitHubat commit ea2c202

Used in 2 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in TencentCloudBase/CloudBase-AI-Toolkit, which our catalogue first saw on October 7, 2026.

• aiskillstore/marketplaceskills/tencentcloudbase/cloudbase-agent/py
• infometa/workbuddyskillsskills/cloudbase/references/cloudbase-agent/pyconnectors/cloudbase/skills/references/cloudbase-agent/py