MCP
未申請MCP server with 41 AI-powered tools for child safety, fraud detection, and content moderation. Detects bullying, grooming, sextortion, romance scams, social engineering, and more. For Claude, Cursor, and MCP-compatible AI assistants.
01 / クライアントを選択
03 / 設定を追加
claude mcp add --transport stdio 'tuteliq-mcp' -- 'npx' '-y' '@tuteliq/mcp'04 / クライアントで確認
クライアントの MCP 設定で接続とツール一覧を確認してください。設定のコピーだけでは接続成功は確認できません。
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このリスティングは公開情報から自動的にインデックスされました。申請することで、ページの編集、互換性の設定、成長ツールのアンロックができます。2分以内に完了します。
このサーバーを申請するセキュリティプロファイル
申請済みおよび認証済みのサーバーは毎週の静的スキャンを受け、コードが到達できる範囲（外部サービス、環境変数、シェルコマンド、エージェント設定フォルダ）と既知のアドバイザリを持つ依存関係が表示されます。このリスティングを申請すると利用できます。 セキュリティプロファイルの仕組み
40 件中 40 件
ドキュメントに記載されたツール (40)
プロジェクトのドキュメントに基づきます。サーバーのハンドシェイクは、各ツールの説明や動作を検証するものではありません。
analyse_multi
Run multiple detection endpoints on a single piece of text in one call
analyze
Quick comprehensive safety check (bullying + unsafe)
analyze_document
Analyze PDF documents for safety concerns — per-page multi-endpoint detection with chain-of-custody hashing (max 50MB, 100 pages)
analyze_emotions
Analyze emotional content and mental state indicators — accepts single text or full conversations
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_voice
Transcribe audio and run safety analysis on the transcript
batch_analyze
Analyze up to 50 items in a single request — all twelve detection types (bullying, grooming, unsafe, emotions, socialengineering, appfraud, romancescam, mulerecruitment, gamblingharm, coercivecontrol, vulnerabilityexploitation, radicalisation) — ideal for bulk triage
batch_review_incidents
Apply one decision across many incidents in a single call
cancel_verification_session
Cancel an active session (no credits consumed)
create_verification_session
Create a session for age or identity verification — returns a URL for the user to complete the flow
create_webhook
Create a new webhook endpoint
detect_app_fraud
Detect app-based fraud (fake investment platforms, phishing apps, subscription traps)
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_coercive_control
Detect coercive control patterns (isolation, financial control, monitoring, threats)
detect_gambling_harm
Detect gambling-related harm indicators (chasing losses, concealment, distress)
detect_grooming
Detect grooming patterns and predatory behavior in conversations
detect_mule_recruitment
Detect money mule recruitment tactics (easy-money offers, bank account sharing)
detect_radicalisation
Detect radicalisation indicators (extremist rhetoric, us-vs-them framing, ideological grooming)
detect_romance_scam
Detect romance scam patterns (love-bombing, financial requests, identity deception)
detect_social_engineering
Detect social engineering tactics (pretexting, urgency fabrication, authority impersonation)
detect_synthetic_audio
Dual-signal forensics: transcript + mel spectrogram vision + quantitative audio statistics
detect_synthetic_image
6-signal forensic pipeline: vision AI, EXIF metadata, pixel stats, C2PA Content Credentials, watermarks, pHash
detect_synthetic_text
Detect AI-generated text across 10 child-safety categories (synthetic CSAM, deepfake scripts, AI grooming)
detect_synthetic_video
5-track analysis: per-frame vision, temporal face consistency, lip-sync correlation, spectral audio, transcript
detect_unsafe
Identify unsafe content (self-harm, violence, explicit material)
detect_vulnerability_exploitation
Detect exploitation of vulnerable individuals (elderly, disabled, financially distressed)
generate_report
Create incident reports from conversations
get_action_plan
Generate age-appropriate guidance for safety situations
get_audit_logs
Query the audit log
get_audit_receipt
Fetch the signed receipt for a past inference
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
get_incidents_overview
Counts by category, severity, source, status and platform over a window
get_verification_session
Poll session status — returns full document intelligence (MRZ, barcode, authenticity, face match, liveness)
list_incidents
Paginated, filterable incident list
list_webhooks
List all configured webhooks
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
update_webhook
Update webhook configuration