SafeNest MCP Server
Provides AI-powered child safety tools to detect bullying, grooming, and unsafe content within digital conversations. It enables AI assistants to perform emotional analysis and generate age-appropriate safety action plans or incident reports.
README
<p align="center"> <img src="./assets/logo.png" alt="Tuteliq" width="200" /> </p>
<h1 align="center">Tuteliq MCP Server</h1>
<p align="center"> <strong>MCP server for Tuteliq - AI-powered child safety tools for Claude</strong> </p>
<p align="center"> <a href="https://www.npmjs.com/package/@tuteliq/mcp"><img src="https://img.shields.io/npm/v/@tuteliq/mcp.svg" alt="npm version"></a> <a href="https://github.com/Tuteliq/mcp/blob/main/LICENSE"><img src="https://img.shields.io/github/license/Tuteliq/mcp.svg" alt="license"></a> </p>
<p align="center"> <a href="https://api.tuteliq.ai/docs">API Docs</a> • <a href="https://tuteliq.app">Dashboard</a> • <a href="https://discord.gg/7kbTeRYRXD">Discord</a> </p>
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 (33)
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) |
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 |
Voice & Image Analysis
| Tool | Description |
|---|---|
analyze_voice |
Transcribe audio and run safety analysis on the transcript |
analyze_image |
Analyze images for visual safety + OCR text extraction |
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 |
Installation
Claude Desktop
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on Mac):
{
"mcpServers": {
"tuteliq": {
"command": "npx",
"args": ["-y", "@tuteliq/mcp"],
"env": {
"TUTELIQ_API_KEY": "your-api-key"
}
}
}
}
Cursor
Add to your Cursor MCP settings:
{
"mcpServers": {
"tuteliq": {
"command": "npx",
"args": ["-y", "@tuteliq/mcp"],
"env": {
"TUTELIQ_API_KEY": "your-api-key"
}
}
}
}
Global Install
npm install -g @tuteliq/mcp
Then run:
TUTELIQ_API_KEY=your-api-key tuteliq-mcp
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"
Get an API Key
- Go to tuteliq.app
- Create an account
- Generate an API key
- Add it to your MCP config
Requirements
- Node.js 18+
- Tuteliq API key
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.
Support
- API Docs: api.tuteliq.ai/docs
- Discord: discord.gg/7kbTeRYRXD
- Email: support@tuteliq.ai
License
MIT License - see LICENSE for details.
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.
<p align="center"> <sub>Built with care for child safety by the <a href="https://tuteliq.ai">Tuteliq</a> team</sub> </p>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.