AI Agents
OpenViking
A self-evolving context database unifying agent memory, RAG, and skills.
★ 39.4k starsAGPL-3.0
View guide →One portable, local-first memory layer for every AI agent - Markdown-native, user-owned and self-evolving.
EverOS is an open-source ai agents project by EverMind-AI (EverMind-AI/EverOS on GitHub). It has 13,367 GitHub stars and 927 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 6 October 2026.
Install the everos package with uv or pip on the machine that will hold the memory.
Run everos init to create ~/.everos/everos.toml, then paste an OpenRouter API key into the [llm] section - that alone unlocks the core Tier 1 memory flow.
Launch everos server start and confirm it with the /health endpoint; capabilities you have not configured report as false and return clear errors if requested.
Post a conversation to /api/v2/memory/add, flush the session to durable Markdown, then search it back - and open ~/.everos to inspect the actual memory files.
Memories persist as plain Markdown files you own and can read, edit and move - the local files are the source of truth, not an opaque database.
One memory layer shared across apps, tools and workflows, running on your machine under your control.
Start with LLM-only keyword search; add an embedding provider for hybrid search, reflection and skill extraction, a reranker for agentic search, and multimodal parsing for images, PDFs, audio and office files.
Add, flush and search endpoints under /api/v2/memory, with session, app and project scoping for multi-app setups.
With the embedding tier, EverOS supports reflection and skill extraction, so memory improves and reusable skills emerge across tasks.
Plugins and integrations for coding CLIs and agent frameworks, including Claude Code, OpenClaw, Hermes Agent, DeepSeek Harness and Dify.
Clone EverOS if you want to develop on it or try the contributor demo; most users install the package instead.
git clone https://github.com/EverMind-AI/EverOS.git
cd EverOSInstall the package, then initialize your memory root and add your OpenRouter key to ~/.everos/everos.toml.
pip install everos # or: uv pip install everos
everos initStart EverOS and verify it is healthy before wiring it into your agent.
everos server start
curl http://127.0.0.1:8000/healthEverOS is developed by EverMind-AI (EverMind) and its open-source ecosystem contributors.
Yes. It is Apache-2.0 licensed and self-hosted on your own machine.
The standard Tier 1 setup uses one OpenRouter key for the memory-extraction LLM, so you pay that provider's usage; the project also ships a no-key educational demo for contributors (uv run everos demo --plain).
EverOS stores memory as user-owned Markdown files with a local runtime and tiered search (keyword, hybrid, agentic), rather than keeping memories primarily as embeddings in a hosted or embedded vector store.
Install everos, run everos init, add an OpenRouter key, start the server, and post your first conversation to /api/v2/memory/add.
A self-evolving context database unifying agent memory, RAG, and skills.
Basic Memory: local-first MCP memory so you and your AI tools build a shared knowledge graph in Markdown
Long-term memory runtime for AI agents — plain Markdown as truth, local ranked retrieval, no API key
Self-improving memory layer that works across AI agent harnesses.
Local-first agentic workspace where Claude Code, Codex and a built-in agent share memory, apps and tools.
Local-first AI memory that runs offline on just 8 GB of RAM.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if EverOS is not the right fit.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Free and open — grab the source, star the repo, and start creating.