parental-control

An open-source MCP (Model Context Protocol) server that gives parents real-time oversight and guardrails over their children's AI agent interactions — without taking away the benefits of AI for learning and creativity.

The Problem

AI assistants are increasingly used by children and teenagers. Unlike parental controls for websites or games, there are no native guardrails for AI conversations. A child could:

• Explore self-harm or suicidal ideation with an AI that responds helpfully

• Get pulled into echo chambers where the AI reinforces extreme views

• Encounter explicit or age-inappropriate content through creative writing prompts

• Develop an unhealthy emotional dependency on an AI companion

Parents have no visibility into these interactions — until now.

Related MCP server: Bastion

Architecture

Child's Claude session
        │
        ▼
┌──────────────────────────────────────┐
│  parental-control  (MCP Server)      │
│  ────────────────────────────────    │
│  policy.ts         ← YAML policy, hot-reload via chokidar
│  classifier.ts     ← Regex-first, LLM second-pass
│  privacy-router.ts ← PII detection, local/cloud routing
│  audit.ts          ← JSON Lines audit log
│  session-tracker.ts← Daily limits, curfew enforcement
│  memory.ts         ← SQLite conversation history
│  approval.ts       ← Hold-for-approval flow
│  notifier.ts       ← Telegram / iMessage / WhatsApp / Email
│  profiles.ts       ← Age-based restriction profiles
└──────────────────────────────────────┘
        │
        ▼
  Parent's phone                  Local Ollama (optional)
(Telegram / iMessage / ...)     http://localhost:11434

The server runs alongside Claude Desktop (or any MCP-compatible agent) and intercepts every message using the check_message tool. When something is flagged, the parent gets an alert — and for critical content, the message is held until the parent responds.

Quick Start

1. Install

npx @gonzih/parental-control

2. Configure Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "parental-control": {
      "command": "npx",
      "args": ["-y", "@gonzih/parental-control"],
      "env": {
        "PARENTAL_CONTROL_CHILD_NAME": "Alex",
        "PARENTAL_CONTROL_CHILD_AGE": "14",
        "NOTIFICATION_CHANNEL": "telegram",
        "TELEGRAM_BOT_TOKEN": "your-bot-token-here",
        "TELEGRAM_PARENT_CHAT_ID": "your-chat-id-here"
      }
    }
  }
}

3. Get a Telegram Bot

1. Message @BotFather on Telegram

2. Run /newbot and follow the prompts

3. Copy the bot token into TELEGRAM_BOT_TOKEN

4. Start a chat with your bot, then visit https://api.telegram.org/bot<TOKEN>/getUpdates to find your chat ID

4. Instruct Claude

Add a system prompt to Claude (or your child's agent) that instructs it to use the MCP tools:

You have access to a parental-control MCP server. Before responding to any message:
1. Call check_message with the user's message (role: "user")
2. If the decision is "block", do not respond to that topic
3. If the decision is "hold_for_approval", wait for the approval result
4. Before sending your response, call check_message with your response (role: "assistant")
5. Proceed based on the decision

Configuration

Notification Channels

Telegram (recommended)

NOTIFICATION_CHANNEL=telegram
TELEGRAM_BOT_TOKEN=1234567890:ABCdef...
TELEGRAM_PARENT_CHAT_ID=987654321

iMessage (macOS only)

NOTIFICATION_CHANNEL=imessage
IMESSAGE_PARENT_PHONE=+15555555555

Requires macOS with Messages app configured.

WhatsApp (via Twilio)

NOTIFICATION_CHANNEL=whatsapp
TWILIO_ACCOUNT_SID=ACxxxxxxxx
TWILIO_AUTH_TOKEN=your-auth-token
TWILIO_WHATSAPP_FROM=whatsapp:+14155238886
TWILIO_WHATSAPP_TO=whatsapp:+15555555555

Email (SMTP)

NOTIFICATION_CHANNEL=email
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
SMTP_USER=you@gmail.com
SMTP_PASS=your-app-password
SMTP_PARENT_EMAIL=you@gmail.com

Policy File (recommended)

The easiest way to configure the server is with a YAML policy file at ~/.parental-control/policy.yaml. Copy the example to get started:

cp policy.yaml.example ~/.parental-control/policy.yaml

The server watches this file and hot-reloads it without a restart. You can also force a reload:

npx @gonzih/parental-control --reload-policy

See policy.yaml.example for all options.

All Environment Variables

MCP Tools

check_message

The primary tool. Call this before processing any message.

Input:

{
  "content": "the message text",
  "role": "user",
  "profileId": "optional-profile-id"
}

Output:

{
  "decision": "allow",
  "category": "safe",
  "confidence": 1.0,
  "reason": "No concerning content detected"
}

When held for approval:

{
  "decision": "hold_for_approval",
  "category": "self_harm",
  "confidence": 0.95,
  "reason": "Self-harm content detected: \"hurt myself\"",
  "held": true,
  "approved": false,
  "safeDeflection": "I'd like to pause on this topic..."
}

log_interaction

Log messages to conversation history without classification (for audit trails).

resolve_approval

Approve or deny a held message programmatically (parents can also use Telegram bot commands).

list_pending

Get all messages currently waiting for parent approval.

update_profile

Modify child profile settings at runtime.

get_risk_summary

Get the current spiral risk score and conversation flags.

Decision Types

Content Categories

Safety-Critical (always held or blocked)

• suicide — Suicidal ideation, crisis content

• self_harm — Self-injury content

• explicit_sexual — Pornography, explicit sexual content

• extremist_content — Radicalization, hate groups, terrorism

Age-Gated (vary by profile)

• violence — Instructions for harm, weapons

• substance_abuse — Drug use, drug acquisition

• age_restricted — Alcohol, gambling sites, fake IDs

• gambling — Casino, betting, lottery content

Behavioral Patterns (notify by default)

• spiral_detected — Repeated hopelessness, worthlessness, isolation themes

• echo_chamber — AI reinforcing extreme or one-sided beliefs

• sycophantic_amplification — AI escalating negative emotions

• emotional_manipulation — Urgency, fear, dependency patterns

• identity_crisis — Intense identity struggle signals

• minor_inappropriate — Mildly age-inappropriate content

Age-Based Default Profiles

The server automatically applies age-appropriate defaults:

Under 13

• Blocked: explicit sexual, violence, extremist content, substance abuse, gambling

• Held: self-harm, suicide, age-restricted

• Notify: spiral detected, echo chamber, emotional manipulation, identity crisis

Ages 13–15

• Blocked: explicit sexual, extremist content, gambling

• Held: self-harm, suicide, violence, substance abuse

• Notify: spiral detected, echo chamber, age-restricted, emotional manipulation

Ages 16–17

• Blocked: explicit sexual, extremist content

• Held: self-harm, suicide

• Notify: spiral detected, echo chamber, violence, substance abuse, gambling

Spiral Detection

Spiral detection is a stateful feature that analyzes conversation history for sustained negative thought patterns — not just individual flagged messages.

How it works:

1. Every message is stored in SQLite with a timestamp

2. When check_message is called, the server looks back at the last N messages (default: 20)

3. Pattern matching scores each message for hopelessness, worthlessness, isolation themes

4. If the cumulative score exceeds the threshold, a spiral_detected alert is sent

Patterns detected:

• "nobody loves/likes me"

• "I'm worthless/hopeless/a failure"

• "nothing will ever change"

• "I give up"

• "life is pointless"

• And more (see src/keywords.ts)

Approval Flow

When a message is held for approval:

1. Parent receives notification via their configured channel

2. For Telegram: notification includes /approve <id> and /deny <id> commands

3. Server polls Telegram for responses (30-second long-polling)

4. If no response within timeout (default: 30 min), message is auto-denied

5. Child's AI receives the decision and either:

   • Proceeds normally (approved)

   • Responds with a safe deflection message (denied)

Parent Guidance

Every alert includes actionable guidance tailored to the category. Examples:

For spiral detection:

Find a calm, private moment. Start with: "I've noticed you seem a bit heavy lately — I'm here if you want to talk." Don't ask yes/no questions. Listen first, problem-solve second.

For self-harm:

Call or text 988 (Suicide & Crisis Lifeline) for guidance on how to help. Remove obvious means of self-harm from the home temporarily. Stay connected — check in frequently.

For explicit content:

Stay calm — panic may shut down communication. This is an opportunity, not a crisis. Frame it around safety and healthy relationships, not punishment.

Out-of-Process Enforcement

Classification runs entirely outside the child model's context. Even if the child's AI session is jailbroken or manipulated, it cannot influence the safety decision:

1. First pass — regex + keyword matching (fast, zero cost, prompt-injection-proof)

   • Confidence > 0.8 → use result directly, no LLM needed

   • Confidence 0.4–0.8 → escalate to second pass

   • Confidence < 0.4 → allow but log

2. Second pass — LLM classifier (only for edge cases)

   • Routed to local Ollama or Anthropic API based on inference_router setting

   • A separate model from the child's conversation model

Privacy Router

Control where LLM inference happens via inference_router in policy.yaml:

PII detection (regex-based, never LLM-based) catches:

• Social Security numbers (XXX-XX-XXXX)

• Credit card numbers

• Phone numbers

• Email addresses

• Street addresses

Audit Log

Every classification decision is written to ~/.parental-control/audit.log in JSON Lines format:

{"ts":"2026-03-21T10:00:00Z","category":"violence","action":"block","content_snippet":"first 100 chars...","tool":"check_message","session_id":"abc123"}

Generate a daily summary:

npx @gonzih/parental-control --audit-report
# or for a specific date:
npx @gonzih/parental-control --audit-report 2026-03-20

Output:

=== Audit Report for 2026-03-21 ===

Total events: 47

Actions:
  allow: 40
  notify: 4
  block: 2
  hold_for_approval: 1

Categories:
  safe: 40
  spiral_detected: 4
  violence: 2
  self_harm: 1

Session Time Limits

Track daily usage in ~/.parental-control/usage.json. When the daily limit is reached, all tool calls are blocked and the parent receives a notification:

"Daily limit reached: Alex has used 120 minutes today."

Curfew hours are also enforced — no AI access between curfew_start and curfew_end (supports overnight curfews like 21:00–08:00).

Privacy & Data

• All conversation history is stored locally in SQLite (~/.parental-control/db.sqlite)

• Audit log at ~/.parental-control/audit.log (JSON Lines, parent-readable)

• Usage tracking at ~/.parental-control/usage.json

• No data is sent to any third-party service except your chosen notification channel

• The database path is configurable via PARENTAL_CONTROL_DB

• With inference_router: local, all AI classification stays on-device via Ollama

Development

git clone https://github.com/gonzih/parental-control
cd parental-control
npm install
npm run build
npm start

Project Structure

src/
  index.ts            — MCP server entry point, CLI flags, tool handlers
  policy.ts           — YAML policy loader with chokidar file watcher
  classifier.ts       — Two-pass: regex-first, LLM second-pass with confidence tiers
  privacy-router.ts   — PII detection (regex), local/cloud inference routing
  audit.ts            — JSON Lines audit log, daily report generator
  session-tracker.ts  — Daily usage tracking, curfew enforcement
  keywords.ts         — Keyword lists and regex patterns
  guidance.ts         — Parent guidance templates
  profiles.ts         — Age-based restriction profiles
  memory.ts           — SQLite persistence layer
  notifier.ts         — Notification dispatch (Telegram/iMessage/WhatsApp/email)
  approval.ts         — Hold-for-approval state machine
policy.yaml.example   — Annotated policy file template

Adding New Categories

1. Add keywords to src/keywords.ts

2. Add the category to the Category union in src/classifier.ts

3. Add classification logic in classifyWithRegex()

4. Add a categoryToDecision() mapping entry

5. Add a guidance template in src/guidance.ts

6. Update default profiles in src/profiles.ts

7. Add the category key to policy.yaml.example

Contributing

Contributions welcome. Please open an issue before submitting a large PR.

Areas that need work:

• LLM-based classification (beyond keyword matching)

• Multi-child profile management UI

• Dashboard for conversation history review

• iOS/Android companion app for parent notifications

• Time-of-day and screen-time limits

License

MIT — see LICENSE file.

Crisis Resources

If you discover your child is in crisis:

• 988 Suicide & Crisis Lifeline: Call or text 988 (US)

• Crisis Text Line: Text HOME to 741741

• International Association for Suicide Prevention: https://www.iasp.info/resources/Crisis_Centres/