Open-source AI coworkers that each get a computer of their own: a browser, files and tools, with every action decided before it happens and recorded after. Bring any AG-UI agent.
Markdown kernel for agent memory and identity
Agent Kernel is a starter repo that teaches an AI coding agent how to keep state in plain files. The agent reads `AGENTS.md`, writes its identity into `IDENTITY.md`, tracks knowledge in `KNOWLEDGE.md`, and stores day-by-day notes in `notes/`. It is meant to be cloned per agent, so each one gets its own memory and history. The README says it works with OpenCode, Claude Code, Codex, Cursor, and Windsurf.
Builders who want Claude Code, Codex, Cursor, or other coding agents to keep memory between sessions.
You can resume work without re-explaining the project, the agent’s identity, or the current state.
What it does
Persistent agent memory
Uses `IDENTITY.md`, `KNOWLEDGE.md`, `knowledge/`, and `notes/` to store identity, facts, and session history.
Append-only session notes
Keeps daily logs in `notes/` so past actions and decisions are preserved instead of rewritten.
Per-agent isolation
Lets you clone the same kernel into separate repos for different agents or domains.
Any-agent compatibility
Works with agents that already read project instruction files like `AGENTS.md`, `CLAUDE.md`, or `.cursorrules`.
kern-ai runtime support
Can be initialized and run with `npx kern-ai init my-agent` and `npx kern-ai tui` for daemon and chat channels.
How to get it
- 1With any coding agent
git clone https://github.com/oguzbilgic/agent-kernel.git my-agent cd my-agent opencode # or claude, codex, cursor, etc.
- 2With kern-ai (daemon + Telegram + Slack)
npx kern-ai init my-agent npx kern-ai tui
README
Agent Kernel
The easiest way to create an AI agent. Clone, start, talk.
Your agent remembers between sessions, takes notes, and builds on past work. No framework, no database — just three markdown files and a git repo.
Works with any AI coding agent: OpenCode, Claude Code, Codex, Cursor, Windsurf, etc.
🚀 kern-ai — a runtime built for agent-kernel. Daemon mode, Telegram, Slack, and one brain across every channel.
npx kern-ai init my-agent
Quick start
With any coding agent:
git clone https://github.com/oguzbilgic/agent-kernel.git my-agent
cd my-agent
opencode # or claude, codex, cursor, etc.
With kern-ai (daemon + Telegram + Slack):
npx kern-ai init my-agent
npx kern-ai tui
That's it. The agent reads the kernel, realizes it's new, asks who you want it to be. You tell it. It remembers.
Memory structure
AGENTS.md ← kernel (generic, don't edit)
IDENTITY.md ← who this agent is (agent maintains)
KNOWLEDGE.md ← index of knowledge files (agent maintains)
knowledge/ ← facts about the world (mutable)
notes/ ← daily session logs (append-only)
Two kinds of memory:
knowledge/— State. Facts about how things are right now. The agent updates these when reality changes.notes/— Narrative. What happened each session — decisions, actions, open items. Append-only. Never modified after the day ends.
Why this works
AI agents already read AGENTS.md (or CLAUDE.md, .cursorrules, etc.) as project instructions. This kernel uses that mechanism to teach the agent how to remember.
The agent doesn't need a database, a vector store, or a custom framework. It just needs:
- A file that says "you are stateful, here's how"
- A git repo to store memory in
- Plain markdown files
Multiple agents
Each agent is its own repo. To create another:
git clone https://github.com/oguzbilgic/agent-kernel.git another-agent
cd another-agent
opencode # or claude, codex, etc.
Same kernel, different identity, different knowledge. You can have a homelab agent, an investing agent, a health agent — all running the same OS.
License
MIT
Files in the repo
- AGENTS.md
- IDENTITY.md
- KNOWLEDGE.md
- README.md
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