AutoGPT

AutoGPT Platform lets you create, deploy, and operate continuous agents using low-code workflows and blocks, with self-hosting options and a cloud-hosted beta waitlist.

Agent PlatformLow-code WorkflowsSelf-hosted + Cloud beta

Overview

What is AutoGPT?

AutoGPT Platform is described as a system that enables the creation, deployment, and management of continuous agents for individuals and businesses.

The docs describe low-code workflows for building agents and “blocks” as the building blocks of workflows (actions/integrations), including connections to external services, data processing tools, AI models, custom scripts/functions, and conditional logic components.

The platform documentation also describes an architecture with an AutoGPT Server (source code, infrastructure, marketplace) and an AutoGPT Frontend (agent builder, workflow management, deployment controls, monitoring/analytics).

Key Features

Low-code workflow building to create complex workflows without extensive coding knowledge
Continuous agents that can run persistently and activate based on configured triggers
Blocks as integrations/actions: blocks represent actions and can include external connections, tools, models, scripts, and logic components
Marketplace components referenced in the platform architecture (as described in the docs)
Dual-license model: MIT for most of the repo, Polyform Shield for the autogpt_platform folder

Common Use Cases

•Automation agents built as workflows for tasks like data processing, scheduling, notifications, and tool-to-tool integration
•Long-running processes where structured execution is required
•Using blocks to connect systems (external services + data processing + AI models) inside agent workflows

Who It's For

AutoGPT Platform fits teams or builders who want to design agents as workflows, reuse integrations via blocks, and manage agents via a platform UI (including deployment controls and execution visibility and management controls described in the docs).

How It Works

Main Approach

AutoGPT Platform treats an agent as an automated workflow you design for specific tasks/processes.

Autonomous / Continuous Operation

The docs describe continuous agents that can run persistently and activate based on configured triggers.

Tool Calling and “Blocks”

Blocks are the building blocks of workflows and can represent actions/integrations such as external connections, tools, AI models, scripts/functions, and conditional logic.

Key Differentiators

✓Workflow-first agent building (agents described as workflows)
✓Blocks as a core integration/action unit (including external connections, tools, and models)
✓Marketplace + UI management (agent builder, workflow management, deployment controls, execution visibility and management controls)
✓Dual-licensed approach (MIT + Polyform Shield for autogpt_platform)

Pricing & Plans

AutoGPT’s platform documentation points to a cloud-hosted beta waitlist and self-hosting docs, but it does not state public pricing on the Platform overview page.

Getting Started

Read the official AutoGPT documentation

Quick Start

1Read the official getting started docs for self-hosting guidance
2Set up the AutoGPT Server + Frontend (as the two main platform components described)
3Create an agent by building a workflow with blocks, then manage it via the frontend UI

Get Started with AutoGPT

When to Use AutoGPT

AutoGPT vs LangChain

AutoGPT Platform is positioned as a platform with a UI for building and operating continuous agents via workflows, while LangChain is primarily a code-first framework for composing LLM apps/agent logic in Python/TypeScript.

Learn more about LangChain

AutoGPT vs n8n

AutoGPT Platform emphasizes agents as workflows with “blocks” and a platform UI (agent builder, deployment controls, execution visibility and management controls). n8n is a general workflow automation tool; overlap exists in workflow building, but AutoGPT’s docs frame the workflow as the agent itself.

Learn more about n8n

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Last updated: December 2025

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