kontrol-freek-mcp 1.1.0

AI Assumption Firewall — MCP server that catches assumptions, checks past decisions, detects contradictions, and gates human approval.

🔥 Kontrol Freek

AI assumption firewall — an MCP server that catches AI assumptions, verifies them against a project decision log, detects contradictions, scores risk, and gates human approval before the AI proceeds.

What It Does

AI: "I'll use PostgreSQL" (assumption!)
     ↓
check_assumption("Use PostgreSQL", risk="medium", category="architecture")
     ↓
Kontrol Freek: Check past decisions → Contradictions? → Risk score
     ↓
├─ Low risk + past approval → ✅ Auto-approve
├─ Medium risk → 🔍 Ask human (Telegram/Slack/Web/Terminal)
└─ Contradiction or critical → ⛔ Block + notify human

Beyond Existing MCP Servers

Feature	clarify-mcp	CONTINUITY	mcp-human-loop	VantaGate	Kontrol Freek
ctx.elicit() support	✅	❌	❌	❌	✅
SQLite decision log	❌	✅	❌	❌	✅
Risk scoring	❌	❌	✅	❌	✅
Semantic similarity	❌	❌	❌	❌	✅
Contradiction detection	❌	❌	❌	❌	✅
Cryptographic audit	❌	❌	❌	✅	✅
Time-based decay	❌	❌	❌	❌	✅
Multi-channel	❌	❌	❌	✅	✅
Project context analysis	❌	✅	❌	❌	✅
Adaptive policy engine	❌	❌	Basic	Static	Adaptive

---

Installation

Quick Install (pip)

pip install kontrol-freek-mcp

One-Command Setup (Mac / Linux / Windows)

git clone https://github.com/berkbayri/kontrol-freek-mcp.git
cd kontrol-freek-mcp
python install.py

This will:

1. Install the Python package
2. Generate a .env with a random HMAC secret
3. Register a system service (auto-starts on boot, auto-restarts on crash)
4. Configure Claude Code and Claude Desktop

Manual Install

pip install -e ".[full]"     # Full: Telegram + Web + Embeddings
# or
pip install -e ".[lite]"     # Lite: Telegram + Web (no embeddings)
# or
pip install -e .             # Minimal: stdio only

Claude Code Config

The installer uses the Claude Code CLI to register the server globally (works across all projects):

claude mcp add kontrol-freek /path/to/kontrol-freek \
  -e KF_HMAC_SECRET=your-secret \
  -e KF_DB_PATH=/home/you/.kontrol-freek/decisions.db \
  -e KF_AUDIT_PATH=/home/you/.kontrol-freek/audit.jsonl \
  -e KF_TELEGRAM_TOKEN=BOT_TOKEN \
  -e KF_TELEGRAM_CHAT_ID=CHAT_ID \
  --scope user

This writes to ~/.claude.json (the correct global config file). The old ~/.claude/claude_code_config.json path is not read by Claude Code and should not be used.

Claude Desktop Config

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "kontrol-freek": {
      "command": "python",
      "args": ["-m", "kontrol_freek_mcp"],
      "env": { "KF_HMAC_SECRET": "your-secret" }
    }
  }
}

HTTP Server Mode (remote access)

kontrol-freek --transport streamable-http --port 8765

{
  "mcpServers": {
    "kontrol-freek": {
      "transport": "streamable-http",
      "url": "http://localhost:8765/mcp"
    }
  }
}

---

Telegram Bot Setup

1. Message @BotFather → /newbot → get token
2. Add bot to a group or DM it
3. Get chat ID: https://api.telegram.org/bot<TOKEN>/getUpdates
4. Set in .env:

   KF_TELEGRAM_TOKEN=123456:ABC-DEF...
   KF_TELEGRAM_CHAT_ID=987654321
   

Bot Commands

/kf approve abc123         → Approve assumption
/kf reject abc123 Wrong    → Reject with reason
/kf answer abc123 Yes      → Answer a question
/kf stats                  → Show statistics
/kf recent                 → Recent decisions

---

How It Works

Decision Flow

AI → check_assumption(assumption, risk, category)
         │
         ├── Query past decisions (SQLite)
         ├── Compute semantic similarity (TF-IDF or sentence-transformers)
         ├── Contradiction analysis
         ├── Policy engine → auto_approve / review / block
         │
         ├── auto_approve → Log, continue
         ├── review → Ask human → Wait → Log
         └── block → Notify human → Wait for approval/rejection → Log
                         │
                         ├── ctx.elicit() (native MCP)
                         ├── Telegram bot
                         ├── Slack webhook
                         ├── Web dashboard
                         └── Terminal input (fallback)

Policy Rules

Condition	Verdict
Critical risk	⛔ Block — always requires human approval
Contradiction with past decision	⛔ Block
security/architecture/deployment category	🔍 Review
Low risk + ≥78% similarity + past approval	✅ Auto-approve
High risk	🔍 Review
Default	🔍 Review

Time Decay

Older decisions carry less weight:

• 0 days → 1.0 (fully valid)
• 30 days → 0.72
• 90 days → 0.37
• 180 days → 0.14

This prevents stale approvals from auto-approving new assumptions.

Audit Chain

Every action is logged to an HMAC-SHA256 signed, hash-chained JSONL file:

{"action": "human_approve", "text": "Use PostgreSQL", "detail": "Go ahead",
 "decision_id": 42, "ts": "2025-01-15T14:30:00Z", "prev": "a1b2...", "hash": "d4e5..."}

Verify chain integrity:

from kontrol_freek_mcp.audit import AuditTrail
trail = AuditTrail("./audit.jsonl", "your-secret")
valid, count = trail.verify_chain()
print(f"Valid: {valid}, Entries: {count}")

---

Auto-Start & Crash Recovery

python install.py sets up:

Platform	Mechanism	Details
macOS	LaunchAgent	~/Library/LaunchAgents/com.kontrol-freek.mcp.plist — runs at login, KeepAlive on crash
Linux	systemd user service	~/.config/systemd/user/kontrol-freek.service — Restart=on-failure, survives logout via linger
Windows	Task Scheduler	schtasks — runs at logon

The wrapper script includes exponential backoff crash recovery (5s → 10s → 20s → ..., max 10 restarts).

python install.py --status     # Health check
python install.py --uninstall  # Clean removal

---

Project Structure

kontrol-freek-mcp/
├── src/kontrol_freek_mcp/
│   ├── __init__.py          # Package
│   ├── __main__.py          # python -m support
│   ├── server.py            # Main MCP server — 7 tools + 2 resources + 1 prompt
│   ├── db.py                # SQLite decision database
│   ├── policy.py            # Policy engine (risk, decay, rules)
│   ├── similarity.py        # Semantic similarity (embeddings + TF-IDF)
│   ├── notifier.py          # Multi-channel notification routing
│   ├── audit.py             # HMAC-SHA256 hash-chain audit trail
│   ├── web.py               # FastAPI approval dashboard
│   └── telegram_bot.py      # Telegram bot handler
├── tests/test_core.py
├── install.py               # One-command installer (Mac/Linux/Windows)
├── pyproject.toml
├── CLAUDE.md
├── .env.example
└── README.md

License

MIT