Tuteliq MCP

Name: Tuteliq MCP
Author: Tuteliq

by Tuteliqversion 4.2.6i★ –iComputer or cloud

Registry nameai.tuteliq/mcp

Install

Overview

Description from the maker (original English)

Detect grooming, bullying, fraud, and 16+ online threats across text, voice, image, and video.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Computer or cloud
Transport: stdio, Streamable HTTP
Category: Design, images & audio
You need to fill in: TUTELIQ_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 3 of 3 passed
Runs on the maker’s server: what you ask it goes through their server.
You fill in yourself: TUTELIQ_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Runs in the cloudNothing to install; it connects over the internet
npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://api.tuteliq.ai/mcp

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add --transport http tuteliq https://api.tuteliq.ai/mcp

Or run it on your computer

claude mcp add tuteliq --env TUTELIQ_API_KEY=your-value -- npx -y @tuteliq/mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "tuteliq": {
      "url": "https://api.tuteliq.ai/mcp"
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "tuteliq": {
      "type": "http",
      "url": "https://api.tuteliq.ai/mcp"
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "tuteliq": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@tuteliq/mcp"
      ],
      "env": {
        "TUTELIQ_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://api.tuteliq.ai/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

TUTELIQ_API_KEY secret required env
Tuteliq API key from tuteliq.ai

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

The server asks you to sign in before it lists its tools.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain tuteliq.ai (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
✓ Pass
Endpoint responds
Responded in 274 ms (HTTP 401)
✓ Pass
Sign-in with OAuth
Declares OAuth sign-in, so your AI app can take you to log in
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Design, images & audioi

More stars than 0% of the other 2754 servers in this category
Published to the registry more recently than 87% of the other 2754 servers in this category
Basic checks equal to or better than 100% of the other 2754 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Tuteliq MCP safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: TUTELIQ_API_KEY

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (4.2.6) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Let any LLM watch a video locally — and search everything it has ever watched.

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Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Tuteliq MCP Server

MCP server for Tuteliq - AI-powered child safety tools for Claude

API Docs • Dashboard • Trust • Changelog • Discord

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.

Reads context, not just keywords. Every detector understands coded slang, emoji, leetspeak, algospeak, and deliberate filter evasion, and weighs the conversation around a message — so it tells gaming trash-talk apart from targeted harassment instead of drowning your team in false positives. This coded-language resilience is platform-wide (it applies to grooming, fraud, radicalisation, and the rest, not just bullying) and is built from our own research into how bad actors evade moderation. In an internal benchmark of coded-language and filter-evasion cases, Tuteliq detected roughly 1.7x more of them than leading general-purpose moderation APIs (319-case evasion set; vendors unnamed).

Fast mode. Pass verdict_only: true on detect_grooming or detect_bullying to get just the verdict (risk level, flags, recommended action) without the per-message breakdown — lower latency for real-time screening. The verdict itself is unchanged.

Interactive results. In hosts that support MCP Apps, results render as interactive cards rather than walls of JSON — see Interactive widgets below.

Interactive widgets

Twelve widgets return a rendered card instead of raw text in hosts that support MCP Apps (Claude desktop and web, and other MCP-compatible clients). Everywhere else the same data arrives as structuredContent, so nothing depends on the UI.

Every card carries the same frame: a chrome bar naming the tool that produced the result, the result itself, and a footer with the data-handling note and a Trust Center link. In a transcript holding a dozen results, the chrome bar is what tells you which is which.

Widget	Tools
Detection result	`detect_bullying`, `detect_grooming`, `detect_unsafe`, `analyze`, and the other `detect_*` tools
Multi-endpoint	`analyse_multi`
Emotions	`analyze_emotions`
Media	`analyze_voice`, `analyze_image`, `analyze_video`, `analyze_document`
Synthetic media	`detect_synthetic_text`, `detect_synthetic_image`, `detect_synthetic_audio`, `detect_synthetic_video`
Action plan	`get_action_plan`
Incident report	`generate_report`
Incidents overview	`get_incidents_overview`
Incidents list	`list_incidents`
Incident detail	`get_incident`
Incident trends	`get_incident_trends`
Moderation queue	`moderation_queue`

Severity is rankable by colour. The ramp runs monotonically from safe to critical, so two chips can be compared without reading their labels:

Level	Colour
`critical`	`#9C3A29`
`high`	`#C2543A`
`medium`	`#D98A3D`
`low`	`#B7C2D4`
`safe`	`#19B79A`

Design notes. The widgets are deliberately calm. They report on grooming, self-harm, and abuse, and a card that animates or pulses at the reader turns material that is already distressing into an alarm they cannot dismiss. Severity is carried by a rule and a glyph, not by motion. The crisis-support card leads with reassurance rather than the severity colour, and its helpline numbers are the largest targets on the card because transcribing digits under stress is where people fail.

Widgets are read-only renderers by design. Selecting incidents in the list widget assembles the ID list for a batch_review_incidents call you fire yourself — the mutating call still goes through your host's approval step, so the human-in-the-loop stays in the loop.

Working on the widgets

npm run preview:ui   # builds every widget against fixture data

open dist-preview/__preview.html

Widget source lives in ui/src. Design tokens are centralised in ui/src/theme.ts; prefer them over colour literals so the palette stays in one place.

Available Tools (81 MCP)

Safety Detection

Tool	Description
`detect_bullying`	Analyze text for bullying, harassment, and gaming toxicity — including coded slang, emoji, and deliberate filter evasion, with context that tells trash-talk apart from genuine harm
`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
`batch_analyze`	Analyze up to 50 items in a single request — all twelve detection types (bullying, grooming, unsafe, emotions, social_engineering, app_fraud, romance_scam, mule_recruitment, gambling_harm, coercive_control, vulnerability_exploitation, radicalisation) — ideal for bulk triage
`analyze_emotions`	Analyze emotional content and mental state indicators — accepts single text or full conversations
`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 & Document 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)
`analyze_document`	Analyze PDF documents for safety concerns — per-page multi-endpoint detection with chain-of-custody hashing (max 50MB, 100 pages)

Synthetic Content Detection

Tool	Description
`detect_synthetic_text`	Detect AI-generated text across 10 child-safety categories (synthetic CSAM, deepfake scripts, AI grooming)
`detect_synthetic_image`	6-signal forensic pipeline: vision AI, EXIF metadata, pixel stats, C2PA Content Credentials, watermarks, pHash
`detect_synthetic_audio`	Dual-signal forensics: transcript + mel spectrogram vision + quantitative audio statistics
`detect_synthetic_video`	5-track analysis: per-frame vision, temporal face consistency, lip-sync correlation, spectral audio, transcript

Identity & Age Verification

Tool	Description
`create_verification_session`	Create a session for age or identity verification — returns a URL for the user to complete the flow
`get_verification_session`	Poll session status — returns full document intelligence (MRZ, barcode, authenticity, face match, liveness)
`cancel_verification_session`	Cancel an active session (no credits consumed)

These three tools are registered when you run this package yourself. The hosted connector does not serve them.

Incidents & Moderation

Read the incident store, triage a queue, and record moderator decisions. The review tools emit signed receipts for EU AI Act Art 14 human-oversight evidence.

Tool	Description
`get_incidents_overview`	Counts by category, severity, source, status and platform over a window
`list_incidents`	Paginated, filterable incident list
`get_incident`	Full detail for one incident, including the risk trajectory across messages
`get_incident_trends`	Incident volume bucketed by hour, day or week, split by severity
`moderation_queue`	Moderator triage console: the unreviewed queue, the next item, and — optionally — your own analysis trace and recommended decision, rendered for human sign-off. Read-only
`review_incident`	Record a moderator decision (confirm / downgrade / escalate / reclassify / dismiss) with a signed receipt
`batch_review_incidents`	Apply one decision across many incidents in a single call
`get_audit_receipt`	Fetch the signed receipt for a past inference
`get_audit_logs`	Query the audit log

The decision is the moderator's, and the card makes them take it. The action buttons call review_incident through the host, because a moderator clicking "Escalate" *is* the human decision. They do not fire on one click: review_incident persists an override and emits a signed Art 12 audit receipt and requires a reason_code, so the button opens a reason picker and a second click commits. Nothing is ever defaulted into that receipt on the moderator's behalf.

The reasoning, confidence and analysis trace on the card are supplied by the calling assistant and are labelled as such — an argument for a human to weigh, not a Tuteliq measurement.

Pass operator_name to brand the header with the customer or team name. Omit it and the card is unbranded — it is never defaulted to a placeholder.

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
`get_usage_summary`	Get today's usage: requests made, succeeded and failed, remaining today, and the rate limit
`get_usage_quota`	Get real-time rate-limit status — pre-flight check before batch runs

Policy Configuratio

Only the beginning is shown; read the rest in the repo

Tuteliq MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Or run it on your computer

Or run it on your computer

Or run it on your computer

Or run it on your computer

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

What is this?

Interactive widgets

Working on the widgets

Available Tools (81 MCP)

Safety Detection

Fraud & Harm Detection

Voice, Image, Video & Document Analysis

Synthetic Content Detection

Identity & Age Verification

Incidents & Moderation

Webhook Management

Pricing

Usage & Billing

Policy Configuratio