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…
tuteliq-mcp is an MCP project maintained in the tuteliq/mcp repository. The maintainer describes its purpose as “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…”. Read the project documentation for the complete scope.
The maintainer’s configuration uses https://api.tuteliq.ai/mcp. It declares streamable-http transport. Check the project’s account and authentication instructions when adding the endpoint to your client.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| detect_bullying | Analyze text for bullying, harassment, and gaming toxicity — including coded slang, emoji, and deliberate filter evasion, with context that tells trash-talk… |
| 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… |
| 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 |
| 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) |
| 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) |
| 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 |
| 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) |
| 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… |
| 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 | Get audit trail of all data operations |
| 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 |
| get_pricing | Get available pricing plans |
| get_pricing_details | Get detailed pricing with features and limits |
| 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 current billing-period summary (used, limits, purchased credits) |
| get_usage_quota | Get real-time rate-limit status — pre-flight check before batch runs |
| get_policy | Get the account's detection policy (per-category flag/block thresholds, auto-moderation) |
| set_policy | Update the account's detection policy configuration |
| list_policy_rules | List all automation rules (block/flag/escalate/notify/log_only on matching detections) |
| create_policy_rule | Create a rule that acts automatically when detections match its conditions |
| get_policy_rule | Get full detail of a single rule |
| update_policy_rule | Update any subset of a rule's fields (e.g., pause with enabled: false) |
| delete_policy_rule | Permanently delete a rule |
| evaluate_policy_rules | Dry-run rules against a hypothetical detection result |
| get_detection_settings | See which detection endpoints are enabled/disabled + default context |
| update_detection_settings | Enable/disable endpoints, set default context |
| reset_detection_settings | Reset to defaults (all endpoints enabled) |
| get_intelligence_trends | Anonymised network-wide threat trends by endpoint/category/age/platform/geo |
| get_emerging_threats | Emerging threat patterns over a recent window |
| get_weekly_digest | Weekly digest: summary, top categories, notable changes |
| get_risk_trends | Anonymised global risk trends |
| 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) |
| 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 |
{
"mcpServers": {
"tuteliq": {
"type": "http",
"url": "https://api.tuteliq.ai/mcp"
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
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