ReMe vs EverOS
Markdown-based long-term memory for AI agents
ReMe and EverOS are Python projects that give AI agents persistent memory stored in editable Markdown, with indexes for retrieval. ReMe emphasizes a self-evolving knowledge workspace and several service interfaces, while EverOS distinguishes user and agent memory and supports scoped retrieval across workflows.
ReMe: Build a File-Based Memory Workspace for AI Agents
ReMe is a Python memory-management kit for agents, built around a local-first, self-evolving knowledge base stored as Markdown files. It helps agent users capture conversations and resources, refine durable knowledge, and retrieve relevant context across supported agent integrations.
EverOS: Give AI Agents Portable Long-Term Memory
EverOS is a Python memory runtime that stores agent conversations and context in editable Markdown, with local indexes for retrieval. It suits teams building agents that need user-owned memory to persist across apps and sessions.
| ReMe | EverOS | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 3.7k | 13.4k |
| Forks | 321 | 926 |
| Last analyzed | Oct 23, 2026 | Oct 7, 2026 |
Key differences
- ReMe organizes durable knowledge in a personal workspace with frontmatter and wikilinks; EverOS separates user memory, such as episodes and profiles, from agent memory, such as cases and skills.
- ReMe offers BM25 search, wikilink expansion, and optional embeddings; EverOS offers keyword search, with optional embedding-based and hybrid retrieval plus retrieval scopes for users, agents, apps, projects, and sessions.
- ReMe provides CLI, HTTP, MCP, Studio, and Python interfaces; EverOS provides a Python library and API and describes local SQLite and LanceDB indexes.
- ReMe lists integrations including QwenPaw, Claude Code, and Codex; EverOS lists Dify and Raven alongside OpenClaw, Hermes, and DeepSeek Harness.
- ReMe requires Python 3.11 or newer, and basic file operations and BM25 search can work without model credentials; EverOS requires Python 3.12 or newer and an LLM provider for its documented server setup.
- Both projects use Apache-2.0 and are active; the provided repository figures list 3.7k stars and 321 forks for ReMe, compared with 13.4k stars and 926 forks for EverOS.
Choose ReMe if you…
- want a Markdown knowledge workspace with frontmatter, wikilinks, and memory evolution workflows.
- need CLI, HTTP, MCP, Studio, or Python interfaces for workspace operations.
- want to use BM25 search without model credentials for basic file operations and retrieval.
Choose EverOS if you…
- need memory scoped across user, agent, app, project, and session identifiers.
- want Markdown changes synchronized with local SQLite and LanceDB indexes.
- need optional ingestion for images, PDFs, audio, or office documents, with the required configuration.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.