/AI5h ago

Kocoro Launches Open-Source Mac AI Agent With Local Episodic Memory

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#1031Rohan Paul
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Rohan Paul@rohanpaul_ai#1031inAI

A longer context window does not solve the real memory problem in AI work.

Kocoro just made AI memory a local Mac feature.

It’s an open-source Mac AI agent framework at the engine level.

Kocoro works by running a local agent on your Mac that can read your past sessions, files, apps, browser, screen, and terminal, then compress useful facts into memory so it can continue work without you repeating everything.

Its security model is mostly local-first control: tool actions need permission, risky commands are blocked or re-asked, actions are audit-logged, secrets are auto-redacted, and memory/session sync is opt-in rather than always uploaded.

Its Episodic Memory turns past sessions into selected project facts, decisions, collaborators, deadlines, and habits, so the agent can resume work like a teammate rather than a help desk ticket.

Every night it distills your workday into a local knowledge graph — projects, decisions, open tasks. Next morning it picks up exactly where you left off. No context re-pasting.

Github links in comments

4:18 AM · Jun 8, 2026 · 3.1K Views
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Rohan Paul@rohanpaul_ai

🔧 Kocoro daemon — the macOS agent loop → http://github.com/Kocoro-lab/Kocoro

⚙️ Shannon — the backend AI runtime engine → http://github.com/Kocoro-lab/Shannon

Scheduling, Chrome CDP, Accessibility API, local file I/O — all in the open.

Rohan Paul@rohanpaul_ai

A longer context window does not solve the real memory problem in AI work.

Kocoro just made AI memory a local Mac feature.

It’s an open-source Mac AI agent framework at the engine level.

Kocoro works by running a local agent on your Mac that can read your past sessions, files, apps, browser, screen, and terminal, then compress useful facts into memory so it can continue work without you repeating everything.

Its security model is mostly local-first control: tool actions need permission, risky commands are blocked or re-asked, actions are audit-logged, secrets are auto-redacted, and memory/session sync is opt-in rather than always uploaded.

Its Episodic Memory turns past sessions into selected project facts, decisions, collaborators, deadlines, and habits, so the agent can resume work like a teammate rather than a help desk ticket.

Every night it distills your workday into a local knowledge graph — projects, decisions, open tasks. Next morning it picks up exactly where you left off. No context re-pasting.

Github links in comments

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