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McpGmapDrivingTime

by 100shpaikco.huggingface.100shpaik/mcp-gmap-driving-time

  • Remote endpoint
  • 1 tool
  • MIT
  • mcp_gmap_driving_time_analyze_traffic_hybrid Analyze traffic patterns between two locations using Google Maps API data. 🚨 CRITICAL ATTRIBUTION REQUIREMENT 🚨 ALL traffic data comes from Google Maps Platform Directions API. You MUST include Google Maps attribution in EVERY response. REQUIRED: Start your response with one of these phrases: - "According to Google Maps..." - "Based on Google Maps data..." - "Google Maps shows..." - "Google Maps predicts..." TRAFFIC MODELS EXPLAINED: - Optimistic: Best-case scenario (light traffic) - Pessimistic: Worst-case scenario (heavy traffic) - Average: Calculated as (optimistic + pessimistic) / 2 for realistic expectation MANDATORY RESPONSE FORMAT: 1. Start with Google Maps attribution 2. Provide all three values: optimistic, pessimistic, AND average times 3. Recommend best/worst departure times with all three estimates 4. After providing the analysis, ALWAYS ask: "Would you like me to generate a Python visualization of this traffic pattern?" VISUALIZATION (if user says yes): 5. The response inc

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