MCPInstall

cabinet-ai-knowledge-base

AI-first knowledge base and startup OS with file-based storage, AI agents, scheduled jobs, and embedded apps

Installs
608
Last 24h
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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/trending-skills --skill cabinet-ai-knowledge-base
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads cabinet-ai-knowledge-base automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Cabinet AI Knowledge Base

Skill by ara.so — Daily 2026 Skills collection.

Cabinet is an AI-first startup OS and knowledge base where everything lives as markdown files on disk. No database, no vendor lock-in — self-hosted with AI agents that have memory, scheduled jobs, embedded HTML apps, git-backed history, and a full web terminal.


Installation

Quick Start (recommended)

npx create-cabinet@latest
cd cabinet
npm run dev:all

Open http://localhost:3000 — the onboarding wizard builds your AI team in 5 questions.

Manual Clone

git clone https://github.com/hilash/cabinet.git
cd cabinet
npm install
cp .env.example .env.local
npm run dev:all

Prerequisites

  • Node.js 20+
  • Claude Code CLI: npm install -g @anthropic-ai/claude-code
  • macOS or Linux (Windows via WSL)

Environment Configuration

# .env.local
KB_PASSWORD=your_optional_password   # Leave empty for no auth
DOMAIN=localhost                     # Or your custom domain

Key Commands

npm run dev          # Next.js dev server on port 3000
npm run dev:daemon   # WebSocket + job scheduler on port 3001
npm run dev:all      # Both servers together (use this for development)
npm run build        # Production build
npm run start        # Production mode (both servers)

Architecture

cabinet/
  src/
    app/api/         → Next.js API routes
    components/      → React components (sidebar, editor, agents, jobs, terminal)
    stores/          → Zustand state management
    lib/             → Storage, markdown, git, agents, jobs
  server/
    cabinet-daemon.ts → WebSocket + job scheduler + agent executor
  data/
    .agents/.library/ → 20 pre-built agent templates
    getting-started/  → Default KB pages

Tech stack: Next.js 16, TypeScript, Tailwind CSS, shadcn/ui, Tiptap, Zustand, xterm.js, node-cron


Project Structure (data directory)

Cabinet stores everything as markdown files under data/:

data/
  getting-started/
    index.md
  my-project/
    index.md
    research.md
    index.html        ← Embedded HTML app (auto-rendered as iframe)
  .agents/
    .library/
      ceo.md
      product-manager.md
      researcher.md
    active/
      my-ceo/
        index.md      ← Agent definition
        memory.md     ← Agent memory (auto-updated)

Agent Definition Format

Agents are defined as markdown files with YAML frontmatter:

---
name: Research Scout
role: researcher
schedule: "0 */6 * * *"   # Cron: every 6 hours
skills:
  - web-search
  - summarization
  - reddit-scout
goals:
  - Monitor competitor activity
  - Surface trending topics in AI tooling
  - File weekly summary reports
---

# Research Scout

You are a research agent for [Company Name]. Your job is to...

## Memory

<!-- Agent memory is auto-appended here by the daemon -->

Creating a Custom Agent

Via the UI

  1. Navigate to the Agents panel in the sidebar
  2. Click "New Agent" and select a template or start blank
  3. Fill in role, goals, and schedule
  4. Cabinet creates data/.agents/active/<agent-name>/index.md

Programmatically

// src/lib/agents.ts pattern — create an agent file directly
import fs from 'fs/promises'
import path from 'path'

const agentDir = path.join(process.cwd(), 'data', '.agents', 'active', 'my-agent')

await fs.mkdir(agentDir, { recursive: true })

await fs.writeFile(
  path.join(agentDir, 'index.md'),
  `---
name: My Custom Agent
role: analyst
schedule: "0 9 * * 1"
goals:
  - Analyze weekly metrics
  - Post summary to #reports channel
---

# My Custom Agent

You are a data analyst agent. Every Monday at 9am you will...
`
)

Scheduled Jobs (Cron)

Agents use standard cron syntax in their frontmatter schedule field:

# Common schedule patterns
schedule: "0 */6 * * *"    # Every 6 hours
schedule: "0 9 * * 1"      # Every Monday at 9am
schedule: "0 8 * * *"      # Every day at 8am
schedule: "*/30 * * * *"   # Every 30 minutes
schedule: "0 0 * * 0"      # Weekly on Sunday midnight

The Cabinet daemon (server/cabinet-daemon.ts) reads agent files and registers jobs via node-cron. Jobs run agent prompts through Claude Code and write results back to the agent's memory file.


Embedded HTML Apps

Drop an index.html in any folder under data/ — Cabinet automatically renders it as an embedded iframe with a full-screen toggle:

data/
  my-dashboard/
    index.html    ← Cabinet renders this as an embedded app
    data.json
    style.css

Example data/my-dashboard/index.html:

<!DOCTYPE html>
<html>
<head>
  <title>Metrics Dashboard</title>
  <style>
    body { font-family: sans-serif; padding: 20px; background: #1a1a1a; color: #eee; }
    .metric { font-size: 2rem; font-weight: bold; color: #55c938; }
  </style>
</head>
<body>
  <h1>Weekly Metrics</h1>
  <div class="metric" id="count">Loading...</div>
  <script>
    fetch('./data.json')
      .then(r => r.json())
      .then(d => document.getElementById('count').textContent = d.value)
  </script>
</body>
</html>

No build step required. Version controlled via git automatically.


Git-Backed History

Every save auto-commits. Cabinet wraps git operations in src/lib/git.ts:

// Auto-commit on every page save (Cabinet handles this internally)
// To access history via the UI:
// 1. Open any page
// 2. Click the history icon in the toolbar
// 3. Browse diffs and restore any version

// To inspect from the shell:
cd data
git log --oneline
git diff HEAD~1 HEAD -- my-project/research.md
git checkout HEAD~5 -- my-project/research.md  # Restore older version

Markdown Page Format

Cabinet pages are standard markdown files with optional frontmatter:

---
title: Competitor Analysis
tags: [research, competitors, q2-2026]
created: 2026-04-07
agent: research-scout
---

# Competitor Analysis

## Summary

...

## Last Updated by Agent

<!-- Agent appends updates here -->

API Routes

Cabinet exposes Next.js API routes under src/app/api/:

// Read a page
GET /api/pages?path=my-project/research

// Save a page
POST /api/pages
Body: { path: "my-project/research", content: "# Research\n..." }

// List directory
GET /api/files?dir=my-project

// Run an agent manually
POST /api/agents/run
Body: { agentId: "research-scout" }

// Get agent status
GET /api/agents/status?id=research-scout

// Search all pages
GET /api/search?q=competitor+analysis

Example: Calling the API from TypeScript

// Read a knowledge base page
const response = await fetch('/api/pages?path=my-project/research')
const { content, path } = await response.json()

// Save a page
await fetch('/api/pages', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    path: 'my-project/research',
    content: '# Research\n\nUpdated content...'
  })
})

// Trigger an agent run
await fetch('/api/agents/run', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ agentId: 'research-scout' })
})

Zustand State Management

Cabinet uses Zustand stores in src/stores/. Key patterns:

// Access the page store in a component
import { usePageStore } from '@/stores/pageStore'

function MyComponent() {
  const { currentPage, savePage, pages } = usePageStore()

  const handleSave = async (content: string) => {
    await savePage({ path: currentPage.path, content })
  }

  return <div>{currentPage?.title}</div>
}

// Access agent store
import { useAgentStore } from '@/stores/agentStore'

function AgentPanel() {
  const { agents, runAgent, agentStatus } = useAgentStore()

  return (
    <ul>
      {agents.map(agent => (
        <li key={agent.id}>
          {agent.name} — {agentStatus[agent.id]}
          <button onClick={() => runAgent(agent.id)}>Run</button>
        </li>
      ))}
    </ul>
  )
}

Pre-Built Agent Templates

Located in data/.agents/.library/. Available roles:

DepartmentAgents
LeadershipCEO, COO, CFO, CTO
ProductProduct Manager, UX Designer
MarketingContent Marketer, SEO Specialist, Social Media, Growth Marketer, Copywriter
EngineeringEditor, QA Agent, DevOps Engineer
Sales & SupportSales Agent, Customer Success
AnalyticsData Analyst
OperationsPeople Ops, Legal Advisor, Researcher

To activate a template:

# Copy a template to active agents
cp data/.agents/.library/researcher.md data/.agents/active/my-researcher/index.md
# Then edit goals and schedule in the copied file

Adding a New Agent Template

<!-- data/.agents/.library/custom-scout.md -->
---
name: Custom Scout
role: researcher
schedule: "0 8 * * *"
skills:
  - web-search
  - summarization
goals:
  - Monitor industry news daily
  - Summarize top 5 findings
  - Append to data/research/daily-digest.md
---

# Custom Scout

You are a research agent. Each morning you will search for recent developments
in [TOPIC] and append a dated summary to the daily digest.

## Instructions

1. Search for "[TOPIC] news" from the last 24 hours
2. Select the 5 most relevant items
3. Write a 2-3 sentence summary per item
4. Append to `data/research/daily-digest.md` with today's date as a heading

## Memory

<!-- Populated automatically -->

Common Patterns

Pattern 1: Knowledge Base with Agent Automation

data/
  company/
    overview.md          ← Human-maintained
    competitors/
      analysis.md        ← Agent-updated weekly
      index.html         ← Auto-generated dashboard
  agents/
    competitor-scout/
      index.md           ← Runs every Monday
      memory.md          ← Tracks what it found last week

Pattern 2: Research Pipeline

1. Researcher agent scouts Reddit/HN every 6h → writes to data/inbox/
2. Analyst agent summarizes inbox daily → writes to data/research/weekly.md
3. CEO agent reads weekly.md every Monday → writes strategic notes

Pattern 3: Using the Web Terminal

The web terminal (xterm.js + node-pty) gives full shell access inside the browser:

  • Press `Ctrl+`` or click the terminal icon in the sidebar
  • Run Claude Code directly: claude "analyze the data in research/competitors.md"
  • Full shell: edit files, run scripts, commit to git

Troubleshooting

Daemon not starting

# Check if port 3001 is in use
lsof -i :3001
# Kill if needed
kill -9 $(lsof -t -i:3001)
# Restart
npm run dev:all

Claude Code not found

npm install -g @anthropic-ai/claude-code
# Verify
claude --version

Agent jobs not running

# Check daemon logs
npm run dev:daemon
# Verify cron syntax at https://crontab.guru
# Check agent frontmatter has valid schedule field

Git history not working

cd data
git status
# If not initialized:
git init
git add .
git commit -m "initial"

Port conflicts

# Next.js uses 3000, daemon uses 3001
# Override in package.json scripts or set PORT env var
PORT=3002 npm run dev

Embedded HTML app not rendering

  • File must be named exactly index.html
  • Must be inside a folder under data/
  • Check browser console for CSP/iframe errors
  • Try accessing directly: http://localhost:3000/apps/my-folder

Self-Hosting in Production

npm run build
npm run start   # Runs both Next.js and daemon in production mode

# With PM2
pm2 start npm --name "cabinet" -- run start
pm2 save
pm2 startup
# Nginx reverse proxy
server {
  listen 80;
  server_name yourdomain.com;

  location / {
    proxy_pass http://localhost:3000;
    proxy_http_version 1.1;
    proxy_set_header Upgrade $http_upgrade;
    proxy_set_header Connection 'upgrade';
    proxy_set_header Host $host;
  }

  location /ws {
    proxy_pass http://localhost:3001;
    proxy_http_version 1.1;
    proxy_set_header Upgrade $http_upgrade;
    proxy_set_header Connection 'upgrade';
  }
}

Resources

FAQ

What does the cabinet-ai-knowledge-base skill do?

AI-first knowledge base and startup OS with file-based storage, AI agents, scheduled jobs, and embedded apps

How do I install cabinet-ai-knowledge-base?

Run npx skills add https://github.com/reason-machines/trending-skills --skill cabinet-ai-knowledge-base in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/cabinet-ai-knowledge-base/ (personal) or .claude/skills/cabinet-ai-knowledge-base/ (project).

Which AI agents can use cabinet-ai-knowledge-base?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is cabinet-ai-knowledge-base safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains cabinet-ai-knowledge-base?

It is published by reason-machines in reason-machines/trending-skills. It has 608 recorded installs.

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