Kernl

Your AI is brilliant — and amnesiac.

Every conversation starts from zero. Your LLM can't see your tasks, read your inbox, check your budget, or remember what you told it yesterday. And the cloud "AI assistants" that promise to fix that? They want your entire life uploaded to their servers.

Kernl fixes both.

What is Kernl?

Kernl is a self-hosted server that plugs your real life into any LLM through the Model Context Protocol (MCP). One endpoint exposes ~290 tools across 60+ modules — tasks, contacts, email, finance, calendar, notes, health, shopping, travel and more — to Claude, Cursor, or any MCP client.

Then it goes past a data bridge: Kernl runs agents — autonomous teams (it calls them offices) that work in loops, call your tools, and finish jobs while you're away.

Everything runs on your machine. Your data never leaves the box.

💬 Talk to your life

Point your AI at Kernl and ask it things it could never do before:

💸 "Did rent clear, and how much did I spend on food this month?" — reads your finance module.

📥 "Triage my inbox and draft replies to anything urgent." — reads your email, writes the drafts.

✅ "What's overdue, and what's due this week?" — straight from your real tasks + calendar.

🤖 "Spin up the dev office and clear the next three backlog items." — launches an agent team that works on its own.

Real data. Real actions. On your machine — not in someone else's cloud.

🎬 See it in action

⚡ Quick start

Zero config. One command. A full stack in ~2 minutes:

git clone https://github.com/fastslack/kernl.git
cd kernl
docker compose up -d --build

→ Dashboard at http://localhost:3086 · MCP endpoint at http://localhost:3086/mcp

No API keys, no host paths, no accounts. Add your LLM keys and channels later from Settings → AI. The graph brain (Neo4j) and key-free web search come bundled.

🔥 Why Kernl

⚔️ Kernl vs. the usual options

🧩 What's inside

Your life, addressable by your AI — tasks & projects, contacts/CRM, reminders, email (IMAP/SMTP), finance & budgets, calendar, notes, goals, health & training, shopping, travel, documents… 60+ modules, every one exposed as MCP tools.

A fleet of agents — cooperating agents with chains, schedules and their own workspaces. Package a whole team as an installable .kernlext office, and watch them work in a live 3D office view.

Pluggable everything

• LLM providers — Claude, OpenAI, Grok, LM Studio (local), and more via extensions.
• Sandbox drivers — run agent code in Docker, CubeSandbox, or your own driver.
• Channels — WhatsApp, Telegram, Slack, email, Mattermost and webchat on one notification bus.

Graph intelligence — optional Neo4j + GDS for cross-module relationship analysis.

🔌 MCP integration

Kernl speaks MCP over stdio and Streamable HTTP at the same time, so every client reaches the same tools.

{
  "mcpServers": {
    "kernl": {
      "command": "bun",
      "args": ["run", "bin/mcp-server.ts"],
      "cwd": "/absolute/path/to/kernl/services/kernel"
    }
  }
}

The MCP HTTP transport is at http://localhost:3086/mcp by default (the official Streamable HTTP spec).

🛠️ Build your own

An extension is a folder (or a packaged .kernlext) with a manifest.json plus any of: a backend module (new MCP tools + HTTP routes), agents & offices, agent-scoped skills, a theme, a channel, or a sandbox driver.

Keep operator-specific material — named agents, your WhatsApp, regional scrapers — private under services/kernel/assets/personal-agents/ (gitignored, ideal for a private submodule).

Full guide → docs/architecture/extension-points.md

📦 More install options

Adds the mtwRequest Rust server, the WhatsApp bridge, and host-coupled mounts (so on-host claude_code agents can edit your sibling repos). Needs a few host paths in .env:

git clone https://github.com/fastslack/kernl.git
cd kernl
cp .env.example .env
$EDITOR .env   # set HOST_HOME, HOST_KERNEL_ROOT, HOST_PROJECTS_ROOT,
               # KERNEL_REQUEST_SRC, KERNEL_WHATSAPP_BRIDGE_SRC
docker compose -f docker-compose.full.yml up -d --build

git clone https://github.com/fastslack/kernl.git
cd kernl
bun install --cwd services/kernel   # requires bun >= 1.3
cp .env.example .env
bun run dev                # stdio MCP + HTTP router (delega a services/kernel)

Requirements

• Bun ≥ 1.3 (primary runtime) or Node ≥ 20.
• Docker + Compose (recommended — unlocks the full stack).
• Neo4j 5.x + GDS (optional; Compose starts one for you; Kernl degrades gracefully without it).

Configuration

Everything is environment-driven — copy .env.example to .env. Minimum keys for Docker runs:

Everything else (LLM keys, Neo4j creds, feature toggles) is documented inline in .env.example.

Scripts

Documentation

• docs/GETTING_STARTED.md — first-run walkthrough
• docs/ARCHITECTURE-MAP.md — contributor map · docs/ARCHITECTURE.md — full system guide
• docs/API_DOCS.md — HTTP + MCP surface reference
• docs/DEPLOYMENT.md — production deploys
• docs/CONTRIBUTING.md · docs/SECURITY.md · docs/PRIVACY.md

⭐ Contributing & community

Kernl is Apache-2.0 and built in the open. Star the repo if it's useful, open an issue for bugs and ideas, and say hi in Discussions. Contributions welcome — see docs/CONTRIBUTING.md.

License & credits

Created and maintained by Matias Aguirre — a Matware project. See AUTHORS and NOTICE.

Released under the Apache License 2.0 — fork it, build commercial plugins on top, redistribute, modify. © 2026 Matware.