Comparison
MemOS vs honcho
Verdict
Pick MemOS if memOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks; pick honcho if memory Library for Stateful Agents.
Markdown twin · MemOS alternatives · honcho alternatives
GraphCanon updated 2d
Trust & integrity
| Signal | MemOS | honcho |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2d · github_public_v1 | Very active (0d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2d · github_public_v1 | Not a fork · Organization account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- MemOS
- Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse
- honcho
- Memory library for building stateful agents
Stars
- MemOS
- 11k
- honcho
- 6.7k
Forks
- MemOS
- 994
- honcho
- 824
Open issues
- MemOS
- 84
- honcho
- 163
Language
- MemOS
- TypeScript
- honcho
- Python
Adopt for
- MemOS
- MemOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks.
- honcho
- Memory Library for Stateful Agents
Persona
- MemOS
- -
- honcho
- -
Runtime
- MemOS
- -
- honcho
- -
License
- MemOS
- MemOS is available under the Apache-2.0 license, allowing you to use it freely with certain conditions.
- honcho
- AGPL-3.0
Last pushed
- MemOS
- Aug 18, 2026
- honcho
- Aug 18, 2026
Categories
- MemOS
- AI Agents, Data & Retrieval
- honcho
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- MemOS
- 84
- honcho
- 163
Stars delta
- MemOS
- +497 (30d)
- honcho
- +659 (30d)
Open issues delta
- MemOS
- +4 (30d)
- honcho
- -3 (30d)
Full report
- MemOS
- Trust report
- honcho
- Trust report
Choose MemOS if…
- MemOS is primarily TypeScript; honcho is Python.
- License: MemOS is Apache-2.0, honcho is AGPL-3.0.
- Pricing: Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs..
- Requirements: Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components..
- Tags unique to MemOS: agent, agentic-ai, llm, memory-management.
- If you require ultra-persistent memory management within your application for long-term storage.
When NOT to use MemOS
- If you prefer fully managed solutions and have no preference over where your data is stored (hosted in MemOS Cloud).
- When minimal setup overhead is a critical requirement since self-hosting MemOS necessitates Neo4j and Qdrant for optimal performance.
- In scenarios preferring simpler on-device solutions as MemOS could be more complex to set up compared to other lightweight plugins or services.
Choose honcho if…
- honcho is primarily Python; MemOS is TypeScript.
- License: honcho is AGPL-3.0, MemOS is Apache-2.0.
- Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain.
- Requires managing long-term and contextual memory in AI agents for statefulness.
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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (MemTensor/MemOS) · observed Aug 18, 2026
- GitHub forks (MemTensor/MemOS) · observed Aug 18, 2026
- Last push (MemTensor/MemOS) · observed Aug 18, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (plastic-labs/honcho) · observed Aug 18, 2026
- GitHub forks (plastic-labs/honcho) · observed Aug 18, 2026
- Last push (plastic-labs/honcho) · observed Aug 18, 2026
- License file (AGPL-3.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: MemOS 11k · honcho 6.7k (synced Aug 18, 2026).
Common questions
- What is the difference between MemOS and honcho?
- MemOS: Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose MemOS over honcho?
- Choose MemOS over honcho when MemOS is primarily TypeScript; honcho is Python; License: MemOS is Apache-2.0, honcho is AGPL-3.0; Pricing: Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs.; Requirements: Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components.; Tags unique to MemOS: agent, agentic-ai, llm, memory-management; If you require ultra-persistent memory management within your application for long-term storage.
- When should I choose honcho over MemOS?
- Choose honcho over MemOS when honcho is primarily Python; MemOS is TypeScript; License: honcho is AGPL-3.0, MemOS is Apache-2.0; Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain; Requires managing long-term and contextual memory in AI agents for statefulness.
- When should I avoid MemOS?
- If you prefer fully managed solutions and have no preference over where your data is stored (hosted in MemOS Cloud). When minimal setup overhead is a critical requirement since self-hosting MemOS necessitates Neo4j and Qdrant for optimal performance. In scenarios preferring simpler on-device solutions as MemOS could be more complex to set up compared to other lightweight plugins or services.
- 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 MemOS or honcho more popular on GitHub?
- MemOS has more GitHub stars (10,758 vs 6,703). Stars measure visibility, not whether either tool fits your constraints.
- Are MemOS and honcho open source?
- Yes - both are open-source projects on GitHub (MemOS: Apache-2.0, honcho: AGPL-3.0).
- Where can I find alternatives to MemOS or honcho?
- GraphCanon lists graph-backed alternatives at MemOS alternatives and honcho alternatives (MemOS markdown twin, honcho markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, MemOS or honcho?
- MemOS: 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 MemOS and honcho?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: MemOS trust report; honcho trust report.