--- title: "openagent vs AutoAgent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/haohao-end-openagent-vs-hkuds-autoagent" tools: ["haohao-end-openagent", "hkuds-autoagent"] --- # openagent vs AutoAgent Neutral, constraint-first comparison with live GitHub stats. | | [openagent](/tools/haohao-end-openagent.md) | [AutoAgent](/tools/hkuds-autoagent.md) | | --- | --- | --- | | Tagline | An end-to-end AI agent platform for building, orchestrating, publishing, and operating AI applications. | Fully-Automated & Zero-Code LLM Agent Framework | | Stars | 825 | 9,451 | | Forks | 80 | 1,319 | | Open issues | 45 | 68 | | Language | Python | Python | | Adopt for | OpenAgent is a full-stack platform designed for teams to create, manage, and publish AI applications with a combination of visual workflow authoring, an advanced backend stack (Flask, LangChain/LangGraph), and a Vue 3 UI | AutoAgent is a fully-automated, zero-code framework enabling users to create and deploy language model agents using natural language inputs alone. | | Persona | - | - | | Runtime | - | - | | License | Open-source under MIT License | MIT | | Categories | AI Agents | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openagent](/tools/haohao-end-openagent.md) | [AutoAgent](/tools/hkuds-autoagent.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 13d | 265d | | Open issues (now) | 45 | 68 | | Owner type | User | Organization | | Security scan | No MCP manifest | No lockfile | | Full report | [trust report](/tools/haohao-end-openagent/trust.md) | [trust report](/tools/hkuds-autoagent/trust.md) | **Typed relationship:** openagent _(alternative)_ AutoAgent Both frameworks aim to simplify the development of end-to-end AI agents, but they may have different features or capabilities. ## Decision facts: openagent - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Python 3.11 or higher.; Docker Compose is required for running the application and managing services. - **Adopt for:** OpenAgent is a full-stack platform designed for teams to create, manage, and publish AI applications with a combination of visual workflow authoring, an advanced backend stack (Flask, LangChain/LangGraph), and a Vue 3 UI - **License detail:** Open-source under MIT License ## Decision facts: AutoAgent - **Pricing:** freemium - The tool is available under an MIT license for free usage and distribution, but additional cloud services or support might come at a cost. - **Requirements:** No Docker required as the framework operates on zero-code principles with no dependency on manual software containerization. - **Adopt for:** AutoAgent is a fully-automated, zero-code framework enabling users to create and deploy language model agents using natural language inputs alone. ## Choose when ### Choose openagent if… - Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.11 or higher.; Docker Compose is required for running the application and managing services.. - Both frameworks aim to simplify the development of end-to-end AI agents, but they may have different features or capabilities. - Tags unique to openagent: ai, flask, faiss-vector-database, docker. - - You need a comprehensive solution for building complex AI agents that can handle deep reasoning loops and multi-step tasks using technologies like RAG, A2A delegation. ### Choose AutoAgent if… - Pricing: The tool is available under an MIT license for free usage and distribution, but additional cloud services or support might come at a cost.. - Requirements: No Docker required as the framework operates on zero-code principles with no dependency on manual software containerization.. - Both frameworks aim to simplify the development of end-to-end AI agents, but they may have different features or capabilities. - Tags unique to AutoAgent: llms. - Also covers LLM Frameworks. - - When you need a no-coding solution to develop LLM (Language Model) agents for collaboration or orchestration tasks. ## When NOT to use openagent - - If you are looking for a platform primarily aimed at creating simple chatbots or single-purpose applications without the need for extensive workflow customization and deep reasoning capabilities. - - You prefer tools that do not rely heavily on visual component orchestration, as OpenAgent's strength lies in its visual workflow design environment which may be overkill for simpler use cases. ## When NOT to use AutoAgent - - When customized technical configurations are mandatory for specific use cases as AutoAgent does not offer manual coding or advanced configuration options. - - If you require full control over the generated code, since AutoAgent operates on a zero-code generation mechanism that may limit direct intervention in the detailed coding process. ## Common questions ### What is the difference between openagent and AutoAgent? openagent: An end-to-end AI agent platform for building, orchestrating, publishing, and operating AI applications.. AutoAgent: Fully-Automated & Zero-Code LLM Agent Framework. See the comparison table for live GitHub stats and shared categories. ### When should I choose openagent over AutoAgent? Choose openagent over AutoAgent when Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.11 or higher.; Docker Compose is required for running the application and managing services.; Both frameworks aim to simplify the development of end-to-end AI agents, but they may have different features or capabilities; Tags unique to openagent: ai, flask, faiss-vector-database, docker; - You need a comprehensive solution for building complex AI agents that can handle deep reasoning loops and multi-step tasks using technologies like RAG, A2A delegation. ### When should I choose AutoAgent over openagent? Choose AutoAgent over openagent when Pricing: The tool is available under an MIT license for free usage and distribution, but additional cloud services or support might come at a cost.; Requirements: No Docker required as the framework operates on zero-code principles with no dependency on manual software containerization.; Both frameworks aim to simplify the development of end-to-end AI agents, but they may have different features or capabilities; Tags unique to AutoAgent: llms; Also covers LLM Frameworks; - When you need a no-coding solution to develop LLM (Language Model) agents for collaboration or orchestration tasks. ### When should I avoid openagent? - If you are looking for a platform primarily aimed at creating simple chatbots or single-purpose applications without the need for extensive workflow customization and deep reasoning capabilities. - You prefer tools that do not rely heavily on visual component orchestration, as OpenAgent's strength lies in its visual workflow design environment which may be overkill for simpler use cases. ### When should I avoid AutoAgent? - When customized technical configurations are mandatory for specific use cases as AutoAgent does not offer manual coding or advanced configuration options. - If you require full control over the generated code, since AutoAgent operates on a zero-code generation mechanism that may limit direct intervention in the detailed coding process. ### Is openagent or AutoAgent more popular on GitHub? AutoAgent has more GitHub stars (9,451 vs 825). Stars measure visibility, not whether either tool fits your constraints. ### Are openagent and AutoAgent open source? Yes - both are open-source projects on GitHub (openagent: MIT, AutoAgent: MIT). ### Where can I find alternatives to openagent or AutoAgent? GraphCanon lists graph-backed alternatives at /tools/haohao-end-openagent/alternatives and /tools/hkuds-autoagent/alternatives (/tools/haohao-end-openagent/alternatives.md, /tools/hkuds-autoagent/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 /compare/haohao-end-openagent-vs-hkuds-autoagent.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openagent or AutoAgent? openagent: Active. AutoAgent: Slowing. 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 openagent and AutoAgent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: openagent: /tools/haohao-end-openagent/trust; AutoAgent: /tools/hkuds-autoagent/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=haohao-end-openagent`](/api/graphcanon/graph?tool=haohao-end-openagent) - 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/_