Tuteliq

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What is this?

Tuteliq MCP Server brings AI-powered child safety tools directly into Claude, Cursor, and other MCP-compatible AI assistants. Ask Claude to check messages for bullying, detect grooming patterns, or generate safety action plans.

Available Tools (41 MCP + 2 API-only)

Safety Detection

Tool	Description
detect_bullying	Analyze text for bullying, harassment, or harmful language
detect_grooming	Detect grooming patterns and predatory behavior in conversations
detect_unsafe	Identify unsafe content (self-harm, violence, explicit material)
analyze	Quick comprehensive safety check (bullying + unsafe)
analyse_multi	Run multiple detection endpoints on a single piece of text in one call
analyze_emotions	Analyze emotional content and mental state indicators
get_action_plan	Generate age-appropriate guidance for safety situations
generate_report	Create incident reports from conversations

Fraud & Harm Detection

Tool	Description
detect_social_engineering	Detect social engineering tactics (pretexting, urgency fabrication, authority impersonation)
detect_app_fraud	Detect app-based fraud (fake investment platforms, phishing apps, subscription traps)
detect_romance_scam	Detect romance scam patterns (love-bombing, financial requests, identity deception)
detect_mule_recruitment	Detect money mule recruitment tactics (easy-money offers, bank account sharing)
detect_gambling_harm	Detect gambling-related harm indicators (chasing losses, concealment, distress)
detect_coercive_control	Detect coercive control patterns (isolation, financial control, monitoring, threats)
detect_vulnerability_exploitation	Detect exploitation of vulnerable individuals (elderly, disabled, financially distressed)
detect_radicalisation	Detect radicalisation indicators (extremist rhetoric, us-vs-them framing, ideological grooming)

Voice, Image & Video Analysis

Tool	Description
analyze_voice	Transcribe audio and run safety analysis on the transcript
analyze_image	Analyze images for visual safety + OCR text extraction
analyze_video	Analyze video files for safety concerns via key frame extraction (supports mp4, mov, avi, webm, mkv)

Webhook Management

Tool	Description
list_webhooks	List all configured webhooks
create_webhook	Create a new webhook endpoint
update_webhook	Update webhook configuration
delete_webhook	Delete a webhook
test_webhook	Send a test payload to verify webhook
regenerate_webhook_secret	Regenerate webhook signing secret

Pricing

Tool	Description
get_pricing	Get available pricing plans
get_pricing_details	Get detailed pricing with features and limits

Usage & Billing

Tool	Description
get_usage_history	Get daily usage history
get_usage_by_tool	Get usage by tool/endpoint
get_usage_monthly	Get monthly usage with billing info

GDPR Account

Tool	Description
delete_account_data	Delete all account data (Right to Erasure)
export_account_data	Export all account data as JSON (Data Portability)
record_consent	Record user consent for data processing
get_consent_status	Get current consent status
withdraw_consent	Withdraw a previously granted consent
rectify_data	Correct user data (Right to Rectification)
get_audit_logs	Get audit trail of all data operations

Breach Management

Tool	Description
log_breach	Log a new data breach (starts 72-hour notification clock)
list_breaches	List all data breaches, optionally filtered by status
get_breach	Get details of a specific data breach
update_breach_status	Update breach status and notification progress

Verification (API & SDK only)

These tools are available via the REST API and the @tuteliq/sdk Node SDK — not yet exposed as MCP tools.

Tool	Description
verify_age	Verify a user's age via document analysis, biometric estimation, or both. Methods: document, biometric, combined. Returns verified age range, confidence score, and minor status. Beta — requires Pro tier. 5 credits per call.
verify_identity	Confirm user identity with document authentication, face matching, and liveness detection. Returns match score, liveness result, and document authentication status. Beta — requires Business tier. 10 credits per call.

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Common Parameters

Context Fields

All detection tools accept an optional context object. These fields influence severity scoring and classification:

Field	Type	Description
language	string	ISO 639-1 code (e.g., "en", "sv"). Auto-detected if omitted.
ageGroup	string	Age group (e.g., "10-12", "13-15", "under 18"). Triggers age-calibrated scoring.
platform	string	Platform name (e.g., "Discord", "Roblox"). Adjusts detection for platform norms.
relationship	string	Relationship context (e.g., "classmates", "stranger").
sender_trust	string	Sender verification status: "verified", "trusted", or "unknown".
sender_name	string	Name of the sender (used with sender_trust).

sender_trust Behavior

When sender_trust is set to "verified" or "trusted":

• AUTH_IMPERSONATION is fully suppressed — a verified sender cannot be impersonating an authority
• URGENCY_FABRICATION is suppressed for routine time-sensitive information (schedules, deadlines, appointments)
• Content is only flagged if it contains genuinely malicious elements (credential theft, phishing links, financial demands)
• This prevents false positives on legitimate institutional messages (school notifications, hospital reminders, government advisories)

support_threshold

Controls when crisis support resources (helplines, text lines, web resources) are included in the response:

Value	Behavior
low	Include support for Low severity and above
medium	Include support for Medium severity and above
high	(Default) Include support for High severity and above
critical	Include support only for Critical severity

Note: Critical severity always includes support resources regardless of the threshold setting.

analyse_multi Endpoint Values

The analyse_multi tool accepts up to 10 endpoints per call. Valid endpoint values:

Endpoint ID	Description
bullying	Bullying and harassment detection
grooming	Grooming pattern detection
unsafe	Unsafe content detection (self-harm, violence, explicit material)
social-engineering	Social engineering and pretexting
app-fraud	App-based fraud patterns
romance-scam	Romance scam patterns
mule-recruitment	Money mule recruitment
gambling-harm	Gambling-related harm
coercive-control	Coercive control patterns
vulnerability-exploitation	Exploitation of vulnerable individuals
radicalisation	Radicalisation indicators

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Installation

Claude Desktop (Recommended)

1. Open Claude Desktop and go to Settings > Connectors
2. Click Add custom connector
3. Set the name to Tuteliq and the URL to:

   https://api.tuteliq.ai/mcp
   

4. When prompted, enter your Tuteliq API key

That's it — Tuteliq tools will be available in your next conversation.

Cursor

Add to your Cursor MCP settings:

{
  "mcpServers": {
    "tuteliq": {
      "url": "https://api.tuteliq.ai/mcp",
      "headers": {
        "Authorization": "Bearer your-api-key"
      }
    }
  }
}

Other MCP clients (npx)

For clients that support stdio transport:

{
  "mcpServers": {
    "tuteliq": {
      "command": "npx",
      "args": ["-y", "@tuteliq/mcp"],
      "env": {
        "TUTELIQ_API_KEY": "your-api-key"
      }
    }
  }
}

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Usage Examples

Once configured, you can ask Claude:

Bullying Detection

"Check if this message is bullying: 'Nobody likes you, just go away'"

Response:

## ⚠️ Bullying Detected

**Severity:** 🟠 Medium
**Confidence:** 92%
**Risk Score:** 75%

**Types:** exclusion, verbal_abuse

### Rationale
The message contains direct exclusionary language...

### Recommended Action
`flag_for_moderator`

Grooming Detection

"Analyze this conversation for grooming patterns..."

Quick Safety Check

"Is this message safe? 'I don't want to be here anymore'"

Emotion Analysis

"Analyze the emotions in: 'I'm so stressed about school and nobody understands'"

Action Plan

"Give me an action plan for a 12-year-old being cyberbullied"

Incident Report

"Generate an incident report from these messages..."

Voice Analysis

"Analyze this audio file for safety: /path/to/recording.mp3"

Image Analysis

"Check this screenshot for harmful content: /path/to/screenshot.png"

Webhook Management

"List my webhooks" "Create a webhook for critical incidents at https://example.com/webhook"

Usage

"Show my monthly usage"

Fraud Detection

"Check this message for social engineering: 'Your account will be suspended unless you verify now'" "Is this a romance scam? 'I know we just met online but I need help with a medical bill'"

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Get Started (Free)

1. Create a free Tuteliq account
2. Go to your Dashboard and generate an API Key
3. For Claude Desktop and other MCP plugins, generate a Secure Token under Settings > Plugins
4. Use the API key for direct API/SDK access, or the Secure Token when connecting via MCP

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Requirements

• Node.js 18+
• Tuteliq API key

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Supported Languages (27)

Language is auto-detected when not specified. Beta languages have good accuracy but may have edge cases compared to English.

Language	Code	Status
English	en	Stable
Spanish	es	Beta
Portuguese	pt	Beta
French	fr	Beta
German	de	Beta
Italian	it	Beta
Dutch	nl	Beta
Polish	pl	Beta
Romanian	ro	Beta
Turkish	tr	Beta
Greek	el	Beta
Czech	cs	Beta
Hungarian	hu	Beta
Bulgarian	bg	Beta
Croatian	hr	Beta
Slovak	sk	Beta
Slovenian	sl	Beta
Lithuanian	lt	Beta
Latvian	lv	Beta
Estonian	et	Beta
Maltese	mt	Beta
Irish	ga	Beta
Swedish	sv	Beta
Norwegian	no	Beta
Danish	da	Beta
Finnish	fi	Beta
Ukrainian	uk	Beta

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Best Practices

Message Batching

The bullying and unsafe content tools analyze a single text field per request. If you're analyzing a conversation, concatenate a sliding window of recent messages into one string rather than sending each message individually. Single words or short fragments lack context for accurate detection and can be exploited to bypass safety filters.

The grooming tool already accepts a messages[] array and analyzes the full conversation in context.

PII Redaction

Enable PII_REDACTION_ENABLED=true on your Tuteliq API to automatically strip emails, phone numbers, URLs, social handles, IPs, and other PII from detection summaries and webhook payloads. The original text is still analyzed in full — only stored outputs are scrubbed.

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Supported Languages

Tuteliq supports 27 languages with automatic detection — no configuration required.

English (stable) and 26 beta languages: Spanish, Portuguese, Ukrainian, Swedish, Norwegian, Danish, Finnish, German, French, Dutch, Polish, Italian, Turkish, Romanian, Greek, Czech, Hungarian, Bulgarian, Croatian, Slovak, Lithuanian, Latvian, Estonian, Slovenian, Maltese, and Irish.

All 24 EU official languages + Ukrainian, Norwegian, and Turkish. Each language includes culture-specific safety guidelines covering local slang, grooming patterns, self-harm coded vocabulary, and filter evasion techniques.

See the Language Support docs for details.

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Support

• API Docs: docs.tuteliq.ai
• Discord: discord.gg/7kbTeRYRXD
• Email: [email protected]

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License

MIT License - see LICENSE for details.

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Get Certified — Free

Tuteliq offers a free certification program for anyone who wants to deepen their understanding of online child safety. Complete a track, pass the quiz, and earn your official Tuteliq certificate — verified and shareable.

Three tracks available:

Track	Who it's for	Duration
Parents & Caregivers	Parents, guardians, grandparents, teachers, coaches	~90 min
Young People (10–16)	Young people who want to learn to spot manipulation	~60 min
Companies & Platforms	Product managers, trust & safety teams, CTOs, compliance officers	~120 min

Start here → tuteliq.ai/certify

• 100% Free — no login required
• Verifiable certificate on completion
• Covers grooming recognition, sextortion, cyberbullying, regulatory obligations (KOSA, EU DSA), and more

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The Mission: Why This Matters

Before you decide to contribute or sponsor, read these numbers. They are not projections. They are not estimates from a pitch deck. They are verified statistics from the University of Edinburgh, UNICEF, NCMEC, and Interpol.

• 302 million children are victims of online sexual exploitation and abuse every year. That is 10 children every second. (Childlight / University of Edinburgh, 2024)
• 1 in 8 children globally have been victims of non-consensual sexual imagery in the past year. (Childlight, 2024)
• 370 million girls and women alive today experienced rape or sexual assault in childhood. An estimated 240–310 million boys and men experienced the same. (UNICEF, 2024)
• 29.2 million incidents of suspected child sexual exploitation were reported to NCMEC's CyberTipline in 2024 alone — containing 62.9 million files (images, videos). (NCMEC, 2025)
• 546,000 reports of online enticement (adults grooming children) in 2024 — a 192% increase from the year before. (NCMEC, 2025)
• 1,325% increase in AI-generated child sexual abuse material reports between 2023 and 2024. The technology that should protect children is being weaponized against them. (NCMEC, 2025)
• 100 sextortion reports per day to NCMEC. Since 2021, at least 36 teenage boys have taken their own lives because they were victimized by sextortion. (NCMEC, 2025)
• 84% of reports resolve outside the United States. This is not an American problem. This is a global emergency. (NCMEC, 2025)

End-to-end encryption is making platforms blind. In 2024, platforms reported 7 million fewer incidents than the year before — not because abuse stopped, but because they can no longer see it. The tools that catch known images are failing. The systems that rely on human moderators are overwhelmed. The technology to detect behavior — grooming patterns, escalation, manipulation — in real-time text conversations exists right now. It is running at api.tuteliq.ai.

The question is not whether this technology is possible. The question is whether we build the company to put it everywhere it needs to be.

Every second we wait, another child is harmed.

We have the technology. We need the support.

If this mission matters to you, consider sponsoring our open-source work so we can keep building the tools that protect children — and keep them free and accessible for everyone.

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