--- title: "openagent vs superduper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/haohao-end-openagent-vs-superduper-io-superduper" tools: ["haohao-end-openagent", "superduper-io-superduper"] --- # openagent vs superduper *GraphCanon updated Aug 21, 2026* ## Verdict Pick openagent if openAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license; pick superduper if superduper provides an extensive end-to-end framework for building custom AI applications and agents, leveraging a variety of technologies including Python and PyTorch. [openagent](https://openllm.cloud) reports 792 GitHub stars, 80 forks, and 46 open issues, last pushed Jul 17, 2026. [superduper](https://superduper.io) has 5.3k stars, 544 forks, and 36 open issues, last pushed Sep 1, 2025. Figures are from public GitHub metadata via [openagent's repository](https://github.com/Haohao-end/openagent) and [superduper's repository](https://github.com/superduper-io/superduper). | | [openagent](/tools/haohao-end-openagent.md) | [superduper](/tools/superduper-io-superduper.md) | | --- | --- | --- | | Tagline | Harness architecture for rapidly building vertical AI agents | End-to-end framework for building custom AI applications and agents. | | Stars | 792 | 5,313 | | Forks | 80 | 544 | | Open issues | 46 | 36 | | Language | Python | Python | | Adopt for | OpenAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license. | Superduper provides an extensive end-to-end framework for building custom AI applications and agents, leveraging a variety of technologies including Python and PyTorch. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Data & Retrieval, Vector Databases | AI Agents, Data & Retrieval, Developer Tools, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openagent](/tools/haohao-end-openagent.md) | [superduper](/tools/superduper-io-superduper.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 34d | 352d | | Open issues (now) | 46 | 36 | | Stars delta | +21 (30d) | +9 (30d) | | Open issues delta | +1 (30d) | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/haohao-end-openagent/trust.md) | [trust report](/tools/superduper-io-superduper/trust.md) | ## Decision facts: openagent - **Adopt for:** OpenAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license. ## Decision facts: superduper - **Requirements:** Support for specific database backends can be configured via plugins. - **Adopt for:** Superduper provides an extensive end-to-end framework for building custom AI applications and agents, leveraging a variety of technologies including Python and PyTorch. ## Choose when ### Choose openagent if… - License: openagent is MIT, superduper is Apache-2.0. - Tags unique to openagent: agent, celery, deepagents, deepresearch. - Also covers Vector Databases. - Need integration of OpenAI and Dify functionalities. ### Choose superduper if… - License: superduper is Apache-2.0, openagent is MIT. - Requirements: Support for specific database backends can be configured via plugins.. - Tags unique to superduper: chatbot, data, database, distributed-ml. - Also covers Developer Tools, Inference & Serving, LLM Frameworks, Model Training. - * You require a comprehensive environment for deploying both AI applications and agents that can integrate with MongoDB or similar backends. ## When NOT to use openagent - Projects requiring only basic AI functionality without deep reasoning loops or RAG. - Teams preferring non-Python environments for AI agent development. ## When NOT to use superduper - * If your team is looking for a more specialized tool tailored to specific aspects of ML workflows (e.g., only serving inference), rather than an all-in-one solution like Superduper. - * When Python 3.10+ is not available or feasible in your project environment, as Superduper requires this version to operate. ## Common questions ### What is the difference between openagent and superduper? openagent: Harness architecture for rapidly building vertical AI agents. superduper: End-to-end framework for building custom AI applications and agents.. See the comparison table for live GitHub stats and shared categories. ### When should I choose openagent over superduper? Choose openagent over superduper when License: openagent is MIT, superduper is Apache-2.0; Tags unique to openagent: agent, celery, deepagents, deepresearch; Also covers Vector Databases; Need integration of OpenAI and Dify functionalities. ### When should I choose superduper over openagent? Choose superduper over openagent when License: superduper is Apache-2.0, openagent is MIT; Requirements: Support for specific database backends can be configured via plugins.; Tags unique to superduper: chatbot, data, database, distributed-ml; Also covers Developer Tools, Inference & Serving, LLM Frameworks, Model Training; * You require a comprehensive environment for deploying both AI applications and agents that can integrate with MongoDB or similar backends. ### When should I avoid openagent? Projects requiring only basic AI functionality without deep reasoning loops or RAG. Teams preferring non-Python environments for AI agent development. ### When should I avoid superduper? * If your team is looking for a more specialized tool tailored to specific aspects of ML workflows (e.g., only serving inference), rather than an all-in-one solution like Superduper. * When Python 3.10+ is not available or feasible in your project environment, as Superduper requires this version to operate. ### Is openagent or superduper more popular on GitHub? superduper has more GitHub stars (5,313 vs 792). Stars measure visibility, not whether either tool fits your constraints. ### Are openagent and superduper open source? Yes - both are open-source projects on GitHub (openagent: MIT, superduper: Apache-2.0). ### Where can I find alternatives to openagent or superduper? GraphCanon lists graph-backed alternatives at [openagent alternatives](/tools/haohao-end-openagent/alternatives) and [superduper alternatives](/tools/superduper-io-superduper/alternatives) ([openagent markdown twin](/tools/haohao-end-openagent/alternatives.md), [superduper markdown twin](/tools/superduper-io-superduper/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/haohao-end-openagent-vs-superduper-io-superduper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openagent or superduper? openagent: Steady. superduper: 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 superduper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openagent trust report](/tools/haohao-end-openagent/trust); [superduper trust report](/tools/superduper-io-superduper/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/_