Deploy

PraisonAI offers two deployment approaches: Deploy to Cloud/Docker using praisonai deploy CLI, or Run as a Server locally using Python SDK.

Choose Your Path

Use praisonai deploy to deploy agents to cloud providers or Docker containers.

pip install praisonai
praisonai deploy run --type api

praisonai deploy run --type docker

praisonai deploy run --type cloud --provider aws

praisonai deploy run --type cloud --provider gcp

praisonai deploy run --type cloud --provider azure

Target	Description	Guide
API Server	Local FastAPI server for development	API Guide
Docker	Containerized deployment	Docker Guide
AWS	Deploy to AWS ECS/Fargate	AWS Guide
Azure	Deploy to Azure Container Apps	Azure Guide
GCP	Deploy to Google Cloud Run	GCP Guide

Command	Description
`praisonai deploy run`	Execute deployment
`praisonai deploy init`	Generate agents.yaml with deploy config
`praisonai deploy doctor`	Check deployment readiness
`praisonai deploy status`	View deployment status
`praisonai deploy destroy`	Remove deployment

Start agents as servers locally using Python SDK or CLI.

from praisonaiagents import Agent

agent = Agent(instructions="You are helpful")
agent.launch(port=8000)

from praisonaiagents.mcp import ToolsMCPServer

server = ToolsMCPServer(name="my-tools")
server.run(transport="sse", port=8080)

praisonai --init "helpful assistant"
praisonai --serve --port 8000

Server	Use Case	Guide
Agents	HTTP REST API for single/multi-agent systems	Agents Server
Tools MCP	Expose tools to Claude Desktop, Cursor	Tools MCP
A2A	Agent-to-Agent protocol communication	A2A Server
AGUI	CopilotKit frontend integration	AGUI Server

Documentation for all server endpoints.

I want to…	Use
Test locally	`praisonai deploy run --type api` or `agent.launch()`
Deploy to production	`praisonai deploy run --type cloud --provider <aws/gcp/azure>`
Containerize my agent	`praisonai deploy run --type docker`
Integrate with Claude Desktop	Tools MCP Server
Build a chat UI	AGUI Server with CopilotKit
Connect agents together	A2A Server