# Agents Autogpt

Autonomous AI agent platform for building and deploying continuous agents.

- Repository: https://github.com/davila7/claude-code-templates (33041 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add davila7/claude-code-templates --skill agents-autogpt -g -a claude-code -y`
Codex: `npx skills add davila7/claude-code-templates --skill agents-autogpt -g -a codex -y`
Cursor: `npx skills add davila7/claude-code-templates --skill agents-autogpt -g -a cursor -y`
Gemini CLI: `npx skills add davila7/claude-code-templates --skill agents-autogpt -g -a gemini-cli -y`

## Description

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# AutoGPT - Autonomous AI Agent Platform

Comprehensive platform for building, deploying, and managing continuous AI agents through a visual interface or development toolkit.

## When to use AutoGPT

**Use AutoGPT when:**
- Building autonomous agents that run continuously
- Creating visual workflow-based AI agents
- Deploying agents with external triggers (webhooks, schedules)
- Building complex multi-step automation pipelines
- Need a no-code/low-code agent builder

**Key features:**
- **Visual Agent Builder**: Drag-and-drop node-based workflow editor
- **Continuous Execution**: Agents run persistently with triggers
- **Marketplace**: Pre-built agents and blocks to share/reuse
- **Block System**: Modular components for LLM, tools, integrations
- **Forge Toolkit**: Developer tools for custom agent creation
- **Benchmark System**: Standardized agent performance testing

**Use alternatives instead:**
- **LangChain/LlamaIndex**: If you need more control over agent logic
- **CrewAI**: For role-based multi-agent collaboration
- **OpenAI Assistants**: For simple hosted agent deployments
- **Semantic Kernel**: For Microsoft ecosystem integration

## Quick start

### Installation (Docker)

```bash
# Clone repository
git clone https://github.com/Significant-Gravitas/AutoGPT.git
cd AutoGPT/autogpt_platform

# Copy environment file
cp .env.example .env

# Start backend services
docker compose up -d --build

# Start frontend (in separate terminal)
cd frontend
cp .env.example .env
npm install
npm run dev
```

### Access the platform

- **Frontend UI**: http://localhost:3000
- **Backend API**: http://localhost:8006/api
- **WebSocket**: ws://localhost:8001/ws

## Architecture overview

AutoGPT has two main systems:

### AutoGPT Platform (Production)
- Visual agent builder with React frontend
- FastAPI backend with execution engine
- PostgreSQL + Redis + RabbitMQ infrastructure

The rest: https://github.com/davila7/claude-code-templates/blob/HEAD/cli-tool/components/skills/ai-research/agents-autogpt/SKILL.md