--- title: "agenta vs unbody" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agenta-ai-agenta-vs-unbody-io-unbody" tools: ["agenta-ai-agenta", "unbody-io-unbody"] --- # agenta vs unbody *GraphCanon updated Jul 12, 2026* ## Verdict Pick agenta if agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L; pick unbody if unbody is positioned as a modular, open-source backend for AI-native applications emphasizing dynamic knowledge processing. [agenta](http://www.agenta.ai) reports 4.3k GitHub stars, 565 forks, and 184 open issues, last pushed Jul 11, 2026. [unbody](https://unbody.io) has 527 stars, 49 forks, and 3 open issues, last pushed Apr 14, 2026. Figures are from public GitHub metadata via [agenta's repository](https://github.com/Agenta-AI/agenta) and [unbody's repository](https://github.com/unbody-io/unbody). | | [agenta](/tools/agenta-ai-agenta.md) | [unbody](/tools/unbody-io-unbody.md) | | --- | --- | --- | | Tagline | The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place. | The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data. | | Stars | 4,283 | 527 | | Forks | 565 | 49 | | Open issues | 184 | 3 | | Language | TypeScript | TypeScript | | Adopt for | Agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L | unbody is positioned as a modular, open-source backend for AI-native applications emphasizing dynamic knowledge processing. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | AI Agents, Inference & Serving, LLM Frameworks | AI Agents, Data & Retrieval, Developer Tools, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agenta](/tools/agenta-ai-agenta.md) | [unbody](/tools/unbody-io-unbody.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 88d | | Open issues (now) | 184 | 3 | | Full report | [trust report](/tools/agenta-ai-agenta/trust.md) | [trust report](/tools/unbody-io-unbody/trust.md) | ## Decision facts: agenta - **Adopt for:** Agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L ## Decision facts: unbody - **Adopt for:** unbody is positioned as a modular, open-source backend for AI-native applications emphasizing dynamic knowledge processing. ## Choose when ### Choose agenta if… - License: agenta is Other, unbody is Apache-2.0. - Tags unique to agenta: agents, evaluation, llm-as-a-judge, llm-evaluation. - Also covers Inference & Serving, LLM Frameworks. - You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment. ### Choose unbody if… - License: unbody is Apache-2.0, agenta is Other. - Tags unique to unbody: agentic-ai, ai-native, backend, chatbot. - Also covers Data & Retrieval, Developer Tools, Vector Databases. - unbody ships Docker support for self-hosted deployment. - You need to build an application that requires continuous learning and updating from new data in real-time. ## When NOT to use agenta - Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex. - Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup. ## When NOT to use unbody - If your requirement is for managing static datasets where the information does not evolve over time, like historical sales data analysis. - For projects that do not need advanced integration with AI agents and require only traditional backend functionalities without sophisticated knowledge processing capabilities. ## Common questions ### What is the difference between agenta and unbody? agenta: The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.. unbody: The Supabase of AI era. A modular, open-source backend for building AI-native software — designed for knowledge, not static data.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agenta over unbody? Choose agenta over unbody when License: agenta is Other, unbody is Apache-2.0; Tags unique to agenta: agents, evaluation, llm-as-a-judge, llm-evaluation; Also covers Inference & Serving, LLM Frameworks; You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment. ### When should I choose unbody over agenta? Choose unbody over agenta when License: unbody is Apache-2.0, agenta is Other; Tags unique to unbody: agentic-ai, ai-native, backend, chatbot; Also covers Data & Retrieval, Developer Tools, Vector Databases; unbody ships Docker support for self-hosted deployment; You need to build an application that requires continuous learning and updating from new data in real-time. ### When should I avoid agenta? Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex. Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup. ### When should I avoid unbody? If your requirement is for managing static datasets where the information does not evolve over time, like historical sales data analysis. For projects that do not need advanced integration with AI agents and require only traditional backend functionalities without sophisticated knowledge processing capabilities. ### Is agenta or unbody more popular on GitHub? agenta has more GitHub stars (4,283 vs 527). Stars measure visibility, not whether either tool fits your constraints. ### Are agenta and unbody open source? Yes - both are open-source projects on GitHub (agenta: Other, unbody: Apache-2.0). ### Where can I find alternatives to agenta or unbody? GraphCanon lists graph-backed alternatives at [agenta alternatives](/tools/agenta-ai-agenta/alternatives) and [unbody alternatives](/tools/unbody-io-unbody/alternatives) ([agenta markdown twin](/tools/agenta-ai-agenta/alternatives.md), [unbody markdown twin](/tools/unbody-io-unbody/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/agenta-ai-agenta-vs-unbody-io-unbody.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agenta or unbody? agenta: Very active. unbody: Steady. 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 agenta and unbody? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agenta trust report](/tools/agenta-ai-agenta/trust); [unbody trust report](/tools/unbody-io-unbody/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agenta-ai-agenta`](/api/graphcanon/graph?tool=agenta-ai-agenta) - 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/_