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google-maps

Google Maps integration for OpenClaw with Routes API. Use for: (1) Distance/travel time calculations with traffic prediction, (2) Turn-by-turn directions, (3) Distance matrix between multiple points, (4) Geocoding addresses to coordinates and reverse, (5) Places search and details, (6) Transit planning with arrival times. Supports future departure times, traffic models (pessimistic/optimistic), avoid options (tolls/highways), and multiple travel modes (driving/walking/bicycling/transit).

Why use this skill?

Enhance OpenClaw with Google Maps integration. Get real-time travel times, turn-by-turn directions, multi-stop routing, and geocoding directly within your AI agent workflows.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/shaharsha/google-maps
Or

What This Skill Does

The google-maps skill for OpenClaw is a powerful integration powered by the Google Routes, Places, and Geocoding APIs. It serves as a central hub for geographic data and logistics management. Users can perform complex distance and travel time calculations that account for real-time traffic conditions, generate granular turn-by-turn navigation instructions, calculate distance matrices for multi-stop logistical planning, and geocode addresses into precise coordinates. The skill supports multiple travel modes—including driving, walking, bicycling, and transit—and offers advanced routing features like traffic modeling (optimistic vs. pessimistic), departure/arrival time scheduling, and route avoidance preferences (e.g., tolls or highways).

Installation

To integrate this skill, ensure you have a valid Google Cloud project with the Routes API, Places API, and Geocoding API enabled. Obtain your API key from the Google Cloud Console. Install the skill into your OpenClaw environment using the following command: clawhub install openclaw/skills/skills/shaharsha/google-maps Once installed, configure your credentials in the OpenClaw configuration file:

{
  "env": {
    "GOOGLE_API_KEY": "YOUR_API_KEY_HERE"
  }
}

Use Cases

This skill is designed for individuals and teams needing automated location intelligence. Common use cases include: calculating the optimal commute time for morning meetings, planning multi-leg delivery routes with optimized stops, comparing transit times versus driving in dense metropolitan areas, and batch processing location data for research or business analysis.

Example Prompts

  1. "What is the fastest way to get from my office to the airport by 4 PM, considering potential afternoon traffic?"
  2. "I need to visit three client sites in Chicago today: Downtown, Evanston, and Naperville. Can you give me the best order to visit them to save the most time?"
  3. "Compare the travel time between my home and the train station using bicycling versus walking, avoiding the main highway route."

Tips & Limitations

To ensure accurate results, always utilize the --traffic parameter when planning trips during peak hours, as it significantly impacts transit estimates. When using the matrix command, keep in mind that the size of the origin/destination set can impact cost. Ensure your Google Cloud billing account is active to avoid service interruptions. Note that transit data availability is dependent on local municipal feed updates within Google Maps, which may vary by region.

Metadata

Author@shaharsha
Stars1054
Views0
Updated2026-02-16
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-shaharsha-google-maps": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags

#maps#places#location#navigation#google#traffic#directions#geocoding#routes-api
Safety Score: 4/5

Flags: network-access, external-api

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