--- title: "EverOS vs honcho" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evermind-ai-everos-vs-plastic-labs-honcho" tools: ["evermind-ai-everos", "plastic-labs-honcho"] --- # EverOS vs honcho *GraphCanon updated Aug 18, 2026* ## Verdict Pick EverOS if everOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution; pick honcho if memory Library for Stateful Agents. [EverOS](https://evermind.ai/everos) reports 12k GitHub stars, 891 forks, and 72 open issues, last pushed Aug 17, 2026. [honcho](https://docs.honcho.dev) has 6.7k stars, 824 forks, and 163 open issues, last pushed Aug 18, 2026. Figures are from public GitHub metadata via [EverOS's repository](https://github.com/EverMind-AI/EverOS) and [honcho's repository](https://github.com/plastic-labs/honcho). | | [EverOS](/tools/evermind-ai-everos.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Tagline | One portable memory layer for every AI agent | Memory library for building stateful agents | | Stars | 12,114 | 6,703 | | Forks | 891 | 824 | | Open issues | 72 | 163 | | Language | Python | Python | | Adopt for | EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution. | Memory Library for Stateful Agents | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [EverOS](/tools/evermind-ai-everos.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 72 | 163 | | Stars delta | +849 (30d) | +659 (30d) | | Open issues delta | +16 (30d) | -3 (30d) | | Full report | [trust report](/tools/evermind-ai-everos/trust.md) | [trust report](/tools/plastic-labs-honcho/trust.md) | ## Shared compatibility - **Python**: [EverOS](/tools/evermind-ai-everos.md) - Python runtime; [honcho](/tools/plastic-labs-honcho.md) - Python runtime ## Decision facts: EverOS - **Adopt for:** EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution. ## Decision facts: honcho - **Adopt for:** Memory Library for Stateful Agents ## Choose when ### Choose EverOS if… - License: EverOS is Apache-2.0, honcho is AGPL-3.0. - Tags unique to EverOS: local-first, markdown-native, memory-management, python3. - When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes. ### Choose honcho if… - License: honcho is AGPL-3.0, EverOS is Apache-2.0. - Tags unique to honcho: ai-agents, embeddings, langchain, memory. - honcho ships Docker support for self-hosted deployment. - Requires managing long-term and contextual memory in AI agents for statefulness. ## When NOT to use EverOS - If your project requires a non-markdown-based memory layer, since EverOS is specifically designed for Markdown-format memories and may not integrate well with other formats. - When the requirement is strictly cloud-centric without local-first capabilities; EverOS focuses on being local-first before operating across applications. ## When NOT to use honcho - Do not need complex SDK support or a customizable framework approach. - Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI. ## Common questions ### What is the difference between EverOS and honcho? EverOS: One portable memory layer for every AI agent. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose EverOS over honcho? Choose EverOS over honcho when License: EverOS is Apache-2.0, honcho is AGPL-3.0; Tags unique to EverOS: local-first, markdown-native, memory-management, python3; When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes. ### When should I choose honcho over EverOS? Choose honcho over EverOS when License: honcho is AGPL-3.0, EverOS is Apache-2.0; Tags unique to honcho: ai-agents, embeddings, langchain, memory; honcho ships Docker support for self-hosted deployment; Requires managing long-term and contextual memory in AI agents for statefulness. ### When should I avoid EverOS? If your project requires a non-markdown-based memory layer, since EverOS is specifically designed for Markdown-format memories and may not integrate well with other formats. When the requirement is strictly cloud-centric without local-first capabilities; EverOS focuses on being local-first before operating across applications. ### When should I avoid honcho? Do not need complex SDK support or a customizable framework approach. Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI. ### Is EverOS or honcho more popular on GitHub? EverOS has more GitHub stars (12,114 vs 6,703). Stars measure visibility, not whether either tool fits your constraints. ### Are EverOS and honcho open source? Yes - both are open-source projects on GitHub (EverOS: Apache-2.0, honcho: AGPL-3.0). ### Where can I find alternatives to EverOS or honcho? GraphCanon lists graph-backed alternatives at [EverOS alternatives](/tools/evermind-ai-everos/alternatives) and [honcho alternatives](/tools/plastic-labs-honcho/alternatives) ([EverOS markdown twin](/tools/evermind-ai-everos/alternatives.md), [honcho markdown twin](/tools/plastic-labs-honcho/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/evermind-ai-everos-vs-plastic-labs-honcho.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, EverOS or honcho? EverOS: Very active. honcho: 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 EverOS and honcho? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [EverOS trust report](/tools/evermind-ai-everos/trust); [honcho trust report](/tools/plastic-labs-honcho/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evermind-ai-everos`](/api/graphcanon/graph?tool=evermind-ai-everos) - 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/_