EverOS
Local-first, portable memory layer for AI agents stored as Markdown.
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Use cases
About EverOS
EverOS is listed in our memory & RAG category and is aimed at builders. Local-first, portable memory layer for AI agents stored as Markdown. Pricing, as the maker states it: Open source. Maturity: Mature. We last checked the official link on 2026-10-16.
What is EverOS?
EverOS is a Python library and local-first memory runtime that gives agents one portable memory layer across coding assistants, apps, devices and workflows.
It stores conversations, files and agent trajectories as readable Markdown that you can edit, diff and version in Git, and syncs local SQLite and LanceDB indexes for retrieval.
Sources: the official README and our directory listing, checked 2026-10-18. Official site: evermind.ai/everos.
Who is EverOS for?
Developers who want agent memory they can read, edit and version as plain files.
EverOS at a glance
- Open source: Yes (Apache License 2.0)
- GitHub: EverMind-AI/EverOS · 13,550 stars (as of Oct 21, 2026)
Key features
- Memory stored as Markdown
- Git-versionable
- Local SQLite and LanceDB indexes
- Portable across tools
EverOS FAQ
What is EverOS?
EverOS is a Python library and local-first memory runtime that gives agents one portable memory layer across coding assistants, apps, devices and workflows.
Who is EverOS for?
Developers who want agent memory they can read, edit and version as plain files.
Is EverOS free?
EverOS's pricing, as the maker states it: Open source. Open-source tools are free to use, though you may still pay for model API usage or a hosted plan. Check the official site for current plans.
Is EverOS open source?
Yes. EverOS is released under the Apache License 2.0, according to its GitHub repository.
What are alternatives to EverOS?
Similar tools include AgentMemory, Acontext, MemMachine, projectmem, Pieces and Pixeltable.
EverOS ratings and reviews
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EverOS alternatives
Other memory & RAG tools in our directory. See all memory & RAG tools →
AgentMemory
Persistent memory layer for AI coding agents.
Acontext
Memory layer that stores agent experience as reusable skills.
MemMachine
Universal memory layer for AI agents.
projectmem
A local-first memory layer for coding agents that records issues, attempts, fixes and decisions and warns your agent before it repeats a past mistake.
Pieces
AI memory layer that captures context from your work so you and your AI tools can recover decisions and resume where you left off.
Pixeltable
Multimodal data layer that combines storage, transforms, indexing and retrieval in one Python library for building agents over images, video and documents.
Related lists
🏆 Ranked in: MemPalace alternatives
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🧭 Task guides: Local and self-hosted tools for agent memory
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