EverOS
Open-source agent development and engineering for agent memory, tool use, rag.
What does this agent do, and when should you use it?
The repository describes EverOS as: One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows. This profile is a source-based catalog entry; an independent FARS review is still pending.
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
- Evaluate it for an agent application or engineering workflow.
- Prototype integrations around its documented tools or APIs.
- Inspect the source before adapting it to an existing stack.
What are this agent's strengths and limitations?
- Public source and README are available for inspection.
- Focused on agent memory, tool use, rag.
- Setup, model-provider support, and maturity must be confirmed against the current release.
- No independent FARS score has been assigned yet.
How do you install or deploy this agent?
Follow the current installation instructions in the [repository README](https://github.com/EverMind-AI/EverOS#readme). Requirements and provider setup vary by release.
How do you use this agent?
Start with the examples and quickstart in the [repository documentation](https://github.com/EverMind-AI/EverOS#readme), then test the workflow with limited permissions and non-sensitive data.