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Comparison

EverOS vs mempalace

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 mempalace if mempalace is an open-source AI memory system that leverages ChromaDB as its default vector-store backend, supporting Python 3.9+ and offering both local and server-based embedding options.

Markdown twin · EverOS alternatives · mempalace alternatives

GraphCanon updated Oct 4, 2026

17views this month

EverOS logo

EverOS

EverMind-AI/EverOS

★ 12kpushed Aug 17, 2026
vs
mempalace logo

mempalace

MemPalace/mempalace

★ 59kpushed Sep 18, 2026

Trust & integrity

SignalEverOSmempalace
Maintenance
Very active (1d since push)
As of Aug 18, 2026 · github_public_v1
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Aug 18, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Aug 2, 2026 · osv@v1
No lockfile (source not queried)
As of Oct 4, 2026 · 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
EverOS trust reportmempalace trust reportTrust methodology

Tagline

EverOS
One portable memory layer for every AI agent
mempalace
The best-benchmarked open-source AI memory system

Stars

EverOS
12k
mempalace
59k

Forks

EverOS
891
mempalace
7.6k

Open issues

EverOS
72
mempalace
735

Language

EverOS
Python
mempalace
Python

Adopt for

EverOS
EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution.
mempalace
mempalace is an open-source AI memory system that leverages ChromaDB as its default vector-store backend, supporting Python 3.9+ and offering both local and server-based embedding options.

Persona

EverOS
-
mempalace
-

Runtime

EverOS
-
mempalace
-

License

EverOS
Apache-2.0
mempalace
MIT

Last pushed

EverOS
Aug 17, 2026
mempalace
Sep 18, 2026

Categories

EverOS
AI Agents, Data & Retrieval
mempalace
Data & Retrieval, Vector Databases

Trust and health

Days since push

EverOS
1d
mempalace
0d

Open issues (now)

EverOS
72
mempalace
735

Stars delta

EverOS
+849 (30d)
mempalace
+743 (30d)

Open issues delta

EverOS
+16 (30d)
mempalace
+31 (30d)

Full report

EverOS
Trust report
mempalace
Trust report

Typed relationship

EverOS alternative mempalaceEverOS and Mempalace both aim to provide advanced memory systems for AI agents, with a focus on performance and capability.

Shared compatibility

  • Python · EverOS: Python runtime · mempalace: Python runtime

Choose EverOS if…

  • License: EverOS is Apache-2.0, mempalace is MIT.
  • EverOS and Mempalace both aim to provide advanced memory systems for AI agents, with a focus on performance and capability.
  • Tags unique to EverOS: agent-memory, local-first, long-term-memory, markdown-native.
  • Also covers AI Agents.
  • When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes.

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.
GitHubDetails

Choose mempalace if…

  • License: mempalace is MIT, EverOS is Apache-2.0.
  • EverOS and Mempalace both aim to provide advanced memory systems for AI agents, with a focus on performance and capability.
  • Tags unique to mempalace: ai, chromadb, embedding, llm.
  • Also covers Vector Databases.
  • mempalace ships Docker support for self-hosted deployment.
  • When you need a benchmarked open-source AI memory system that supports a wide range of languages through the embeddinggemma-300m model.

When NOT to use mempalace

  • If you are working in an environment where Python 3.9+ is not available, as mempalace requires this version or higher.
  • When you need a system that does not require at least 300 MB of disk space for the embedding model, as mempalace requires this minimum space for its recommended multilingual model.
GitHubDetails

Explore

EverOS trust report →mempalace trust report →AI Agents category →Data & Retrieval category →Vector Databases category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: EverOS 12k · mempalace 59k (synced Sep 20, 2026).

Common questions

What is the difference between EverOS and mempalace?
EverOS: One portable memory layer for every AI agent. mempalace: The best-benchmarked open-source AI memory system. See the comparison table for live GitHub stats and shared categories.
When should I choose EverOS over mempalace?
Choose EverOS over mempalace when License: EverOS is Apache-2.0, mempalace is MIT; EverOS and Mempalace both aim to provide advanced memory systems for AI agents, with a focus on performance and capability; Tags unique to EverOS: agent-memory, local-first, long-term-memory, markdown-native; Also covers AI Agents; When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes.
When should I choose mempalace over EverOS?
Choose mempalace over EverOS when License: mempalace is MIT, EverOS is Apache-2.0; EverOS and Mempalace both aim to provide advanced memory systems for AI agents, with a focus on performance and capability; Tags unique to mempalace: ai, chromadb, embedding, llm; Also covers Vector Databases; mempalace ships Docker support for self-hosted deployment; When you need a benchmarked open-source AI memory system that supports a wide range of languages through the embeddinggemma-300m model.
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 mempalace?
If you are working in an environment where Python 3.9+ is not available, as mempalace requires this version or higher. When you need a system that does not require at least 300 MB of disk space for the embedding model, as mempalace requires this minimum space for its recommended multilingual model.
Is EverOS or mempalace more popular on GitHub?
mempalace has more GitHub stars (59,143 vs 12,114). Stars measure visibility, not whether either tool fits your constraints.
Are EverOS and mempalace open source?
Yes - both are open-source projects on GitHub (EverOS: Apache-2.0, mempalace: MIT).
Where can I find alternatives to EverOS or mempalace?
GraphCanon lists graph-backed alternatives at EverOS alternatives and mempalace alternatives (EverOS markdown twin, mempalace 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, EverOS or mempalace?
EverOS: Very active. mempalace: 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 mempalace?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: EverOS trust report; mempalace trust report.

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