Deploy

Deploy PraisonAI agents to cloud, Docker, or as local servers

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

Deploy to Cloud

Deploy agents to AWS, Azure, GCP, or Docker

Run as Server

Start HTTP, MCP, A2A, or AGUI servers locally

Deploy to Cloud

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

Warning

The auto-generated api.py (produced by praisonai deploy run --type api) imports bleach to sanitise markdown output before returning it as HTML. Install it alongside praisonai:

bash

pip install praisonai bleach

Without bleach, the generated server fails at startup with ModuleNotFoundError: No module named 'bleach'.

Local API

bash

pip install praisonai bleach
praisonai deploy run --type api
# As of 4.6.34, requires bearer token by default
# See API Server Authentication guide

Docker

bash

praisonai deploy run --type docker

AWS

bash

praisonai deploy run --type cloud --provider aws

GCP

bash

praisonai deploy run --type cloud --provider gcp

Azure

bash

praisonai deploy run --type cloud --provider azure

Cloud Deployment Pages

Target	Description	Guide
API Server	Local FastAPI server for development	API Guide · Auth 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

Deploy CLI Commands

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

Deploy CLI Reference

Complete guide to all praisonai deploy commands and options

New Deploy Surfaces

Local stacks, cloud providers, Kubernetes charts, and one-command scaffolding.

Docker Compose Stack

Local API + Postgres with praisonai deploy compose up

Deploy Templates

Scaffold projects with praisonai deploy create

Deploy to Fly.io

One-command Fly.io deploy

Deploy to Railway

One-command Railway deploy

Deploy to Render

One-command Render deploy

Helm CLI Wrapper

praisonai deploy helm --chart gateway|agents-api

Helm Chart — Agents API

Agents API + Postgres on Kubernetes

Run as Server

Start agents as servers locally using Python SDK or CLI.

Diagram

HTTP Server

python

from praisonaiagents import Agent

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

MCP Server

python

from praisonaiagents import ToolsMCPServer

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

CLI

bash

praisonai serve agents --port 8000

All Serve Commands

Use praisonai serve <type> to start any server. All options in one place:

Command	Protocol	Default Port	Description
`praisonai serve agents`	HTTP	8000	Agents as HTTP REST API
`praisonai serve gateway`	WebSocket	8765	Multi-agent real-time coordination
`praisonai serve mcp`	STDIO/SSE	8080	MCP server for Claude/Cursor
`praisonai serve acp`	STDIO	–	Agent Client Protocol for IDEs
`praisonai serve lsp`	STDIO	–	Language Server Protocol
`praisonai serve ui`	HTTP	8082	Chainlit web interface
`praisonai serve rag`	HTTP	9000	RAG query server
`praisonai serve registry`	HTTP	7777	Package registry server
`praisonai serve docs`	HTTP	3000	Documentation preview
`praisonai serve scheduler`	Background	–	Job scheduler daemon
`praisonai serve recipe`	HTTP	8765	Recipe runner server
`praisonai serve a2a`	JSON-RPC	8082	Agent-to-Agent protocol
`praisonai serve a2u`	SSE	8002	Agent-to-User event stream
`praisonai serve unified`	HTTP/SSE	8765	Agents API + A2A + A2U combined
`praisonai serve openai`	HTTP/SSE	8765	OpenAI API compatibility layer

Unified Serve Reference

Complete guide to all praisonai serve commands and options

Server Type Guides

Server	Use Case	Guide
Unified Serve	All serve commands in one place	Serve Commands
Agents	HTTP REST API for single/multi-agent systems	Agents Server
Gateway	WebSocket multi-agent real-time coordination	Gateway Server
MCP	Expose tools to Claude Desktop, Cursor	MCP Server
A2A	Agent-to-Agent protocol communication	A2A Server
AGUI	CopilotKit frontend integration	AGUI Server

API Reference

Documentation for all server endpoints.

API	Protocol	Reference
Agents API	HTTP REST	Endpoints
MCP API	MCP Protocol	Endpoints
A2A API	JSON-RPC	Endpoints
AGUI API	SSE Streaming	Endpoints

Quick Decision Guide

I want to…	Use
Test locally	`praisonai deploy run --type api` or `agent.launch()` (auto-generated API server prints bearer token on each startup)
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