--- title: "aigis vs AutoGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/killertcell428-aigis-vs-significant-gravitas-autogpt" tools: ["killertcell428-aigis", "significant-gravitas-autogpt"] --- # aigis vs AutoGPT *GraphCanon updated Jul 15, 2026* ## Verdict Pick aigis when license: aigis is Apache-2.0, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, aigis is Apache-2.0. [aigis](https://pypi.org/project/pyaigis/) reports 51 GitHub stars, 8 forks, and 8 open issues, last pushed Jul 14, 2026. [AutoGPT](https://agpt.co) has 185k stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [aigis's repository](https://github.com/killertcell428/aigis) and [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT). | | [aigis](/tools/killertcell428-aigis.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Tagline | Deterministic, zero-dependency Python firewall for AI agents, MCP rug-pull, memory poisoning, indirect injection, exfil channels. 44 compliance templates (US/CN/JP/EU). | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | | Stars | 51 | 185,464 | | Forks | 8 | 46,111 | | Open issues | 8 | 494 | | Language | Python | Python | | Adopt for | - | AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | AI Agents, LLM Frameworks, Vector Databases | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aigis](/tools/killertcell428-aigis.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 8 | 494 | | Owner type | User | Organization | | Full report | [trust report](/tools/killertcell428-aigis/trust.md) | [trust report](/tools/significant-gravitas-autogpt/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. ## Choose when ### Choose aigis if… - License: aigis is Apache-2.0, AutoGPT is Other. - Tags unique to aigis: ai-agent, ai-security, compliance, cybersecurity. - Also covers Vector Databases. - aigis ships Docker support for self-hosted deployment. ### Choose AutoGPT if… - License: AutoGPT is Other, aigis is Apache-2.0. - Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ## When NOT to use aigis - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use AutoGPT - Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. - If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ## Common questions ### What is the difference between aigis and AutoGPT? aigis: Deterministic, zero-dependency Python firewall for AI agents, MCP rug-pull, memory poisoning, indirect injection, exfil channels. 44 compliance templates (US/CN/JP/EU).. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories. ### When should I choose aigis over AutoGPT? Choose aigis over AutoGPT when License: aigis is Apache-2.0, AutoGPT is Other; Tags unique to aigis: ai-agent, ai-security, compliance, cybersecurity; Also covers Vector Databases; aigis ships Docker support for self-hosted deployment. ### When should I choose AutoGPT over aigis? Choose AutoGPT over aigis when License: AutoGPT is Other, aigis is Apache-2.0; Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I avoid aigis? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid AutoGPT? Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ### Is aigis or AutoGPT more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 51). Stars measure visibility, not whether either tool fits your constraints. ### Are aigis and AutoGPT open source? Yes - both are open-source projects on GitHub (aigis: Apache-2.0, AutoGPT: Other). ### Where can I find alternatives to aigis or AutoGPT? GraphCanon lists graph-backed alternatives at [aigis alternatives](/tools/killertcell428-aigis/alternatives) and [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) ([aigis markdown twin](/tools/killertcell428-aigis/alternatives.md), [AutoGPT markdown twin](/tools/significant-gravitas-autogpt/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/killertcell428-aigis-vs-significant-gravitas-autogpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aigis or AutoGPT? aigis: Very active. AutoGPT: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for aigis and AutoGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aigis trust report](/tools/killertcell428-aigis/trust); [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=killertcell428-aigis`](/api/graphcanon/graph?tool=killertcell428-aigis) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_