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Significant-Gravitas AutoGPT

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Stars

187

Active Stable

Forks

46,042

Watchers: 187,116

Language

Python

License: Other

Repository Radar Score

54 / 100

Growth

7d
+0
30d
+0
%
0.0%

Last observed: 6 days ago

Score breakdown

  • popularity 57
  • growth 0
  • activity 90
  • freshness 100
  • community 90

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AutoGPT

AutoGPT — AI agents that finish the work

Get 10 hours back every week.
Describe what you want done. AutoGPT builds the agent, runs it, and reports back.

Get started · Tour · Pricing · Docs · Discord · Self-host


The open-source platform for AI agents

AutoGPT lets you build, deploy, and run AI agents that carry out complete workflows. Describe an outcome in plain English or shape every step in the visual builder, then run the agent on demand, on a schedule, or from a trigger.

185,000+ GitHub stars. Cited by:

“Next frontier of prompt engineering imo: ‘AutoGPTs’.” Andrej Karpathy, founding member of OpenAI
“If you have a phone you can run AutoGPT. You don't even need to learn how to code.” Amjad Masad, co-founder & CEO of Replit
“AutoGPT might be the next big step in AI.” Lior Alexander, CEO of AlphaSignal

Four surfaces, one platform

AutoPilot chat creating an AutoGPT agent
AutoPilot
Describe the job in plain English and turn the conversation into a working agent.
Agents dashboard showing statuses, runs, and costs
Agents
See every agent, run, cost, and action that needs your attention.
AutoGPT Marketplace showing ready-made community agents
Marketplace
Start from proven agents, add one to your library, and customize it for your work.
The AutoGPT Build canvas showing a real agent workflow
Build
Drag, connect, branch, and inspect blocks for exact control over every step.

Get started

AutoGPT Platform — public, hosted, and managed

The hosted Platform is publicly available. We manage the infrastructure, model access, credentials, reliability, and updates so you can focus on the work your agents perform.

Get started on AutoGPT Platform →

Take the interactive tour →

  • AutoPilot, Agents, Marketplace, and Build
  • 45+ connected platforms and hundreds of AI models
  • No model API keys or infrastructure setup
  • Agents that run on demand, on schedules, and from triggers

The hosted Platform is a paid service with usage-based agent runs. Compare plans and pricing →

Self-host AutoGPT

Note

Self-hosting is the free path. You provide the infrastructure and model API keys, and you maintain the deployment. If you want zero setup, use the managed Platform.

macOS and Linux:

curl -fsSL https://setup.agpt.co/install.sh -o install.sh && bash install.sh

Windows PowerShell:

powershell -c "iwr https://setup.agpt.co/install.bat -o install.bat; ./install.bat"

Read the self-hosting guide →


Managed Platform vs. self-hosting

AutoGPT Platform Self-hosted
Access Public signup Clone and install
Cost Paid plan plus agent usage No license fee; pay your own infrastructure and model providers
Setup Managed Docker and configuration required
Model access Built in Bring your own API keys
Updates and operations Managed by AutoGPT Managed by you
Core builder and agent runtime Included Included
Data and infrastructure control Hosted by AutoGPT Runs on your infrastructure
Support Plan-dependent Community support

Both paths use the same repository. Choose the managed Platform when you want agents running immediately; self-host when infrastructure control matters more than operational convenience.


Why the hosted Platform is paid

Every agent run consumes real model usage, compute, storage, secrets management, and operational support. The managed Platform covers that infrastructure and funds continued development of the open-source project.

Self-hosting remains available without a license fee for people and teams that want to provide and operate those resources themselves.


What you can automate

Area Example
Executive operations Prepare a daily brief from internal and external signals
Sales Research every account before tomorrow's meetings
Marketing Turn a launch brief into campaign drafts across channels
Engineering Triage incidents and start with a likely cause
Customer support Draft replies, collect context, and flag escalations
Research Monitor sources and return structured reports when something changes

Integrations

Connect the apps that are yours. AutoGPT provides access to hundreds of AI models and connects agents to 45+ platforms, including:

Gmail · Google Calendar · Google Docs · Google Sheets · GitHub · Slack · Discord · Notion · HubSpot · Linear · Airtable · Jira · Salesforce · Stripe · Webflow

Explore the integrations →


Community and support

Resource Link
Discord Join the AutoGPT community
Documentation docs.agpt.co
Bug reports GitHub Issues
Feature requests GitHub Discussions
Contributing CONTRIBUTING.md

License

Component License What it means
autogpt_platform/ Polyform Shield Free for personal and internal business use; cannot be sold as a competing hosted service
classic/ and everything else MIT Permissive open-source use

AutoGPT Classic

Looking for the original standalone AutoGPT agent? It remains available in classic/ under the MIT License.


Contributors

AutoGPT contributors

Get started with AutoGPT →


Deutsch | Español | français | 日本語 | 한국어 | Português | Русский | 中文

Created: Mar 16, 2023

Last push: Sep 4, 2026

Default branch: master

Latest release: autogpt-platform-beta-v0.7.4

Languages

Share of the codebase by language, based on repository metadata from the host.

  • Python 66.7%
  • TypeScript 31.6%
  • JavaScript 0.5%
  • PLpgSQL 0.4%
  • Shell 0.3%
  • Jinja 0.3%
  • Dockerfile 0.1%
  • CSS 0.1%
  • C 0.1%
  • Batchfile 0.0%
  • Makefile 0.0%
  • Elixir 0.0%
  • HCL 0.0%

Repository Radar analysis

Deterministic insights derived from public metadata and our observations — not personal testing or reviews.

Why this repository is interesting

  • Maintained recently (last push 2 weeks ago).

Who should use it

  • Developers working primarily with Python
  • Teams exploring AI tooling, agents, or ML infrastructure
  • Platform and DevOps engineers
  • Backend engineers shipping APIs and product backends

Potential use cases

  • Reference or evaluate Python open-source approaches in this domain
  • Prototype AI/agent workflows or study reference architectures
  • Evaluate automation, CI/CD, or infrastructure patterns

Strengths

  • Recent repository activity
  • README present in our index
  • Declared license: Other
  • Substantial fork count (46,042) suggests reuse and contribution interest

Limitations / considerations

  • Insights are derived from public metadata and our observations — not a substitute for code review

What to watch

  • Re-check last push, issues, and releases on GitHub before production adoption

Strong signals: Active maintenance

Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.

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