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Awesome-openclaw-skills grounding-lite

Google Maps Grounding Lite MCP for location search, weather, and routes via mcporter.

install
source · Clone the upstream repo
git clone https://github.com/sundial-org/awesome-openclaw-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/grounding-lite" ~/.claude/skills/sundial-org-awesome-openclaw-skills-grounding-lite && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/grounding-lite" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-grounding-lite && rm -rf "$T"
manifest: skills/grounding-lite/SKILL.md
source content

Grounding Lite

Google Maps Grounding Lite MCP provides AI-grounded location data. Experimental (pre-GA), free during preview.

Setup

  1. Enable the API: 
    gcloud beta services enable mapstools.googleapis.com
  2. Get an API key from Cloud Console
  3. Set env: 
    export GOOGLE_MAPS_API_KEY="YOUR_KEY"
  4. Configure mcporter: 
    mcporter config add grounding-lite \
  --url https://mapstools.googleapis.com/mcp \
  --header "X-Goog-Api-Key=$GOOGLE_MAPS_API_KEY" \
  --system

Tools

  • search_places: Find places, businesses, addresses. Returns AI summaries with Google Maps links.
  • lookup_weather: Current conditions and forecasts (hourly 48h, daily 7 days).
  • compute_routes: Travel distance and duration (no turn-by-turn directions).

Commands

# Search places
mcporter call grounding-lite.search_places textQuery="pizza near Times Square NYC"

# Weather
mcporter call grounding-lite.lookup_weather location='{"address":"San Francisco, CA"}' unitsSystem=IMPERIAL

# Routes
mcporter call grounding-lite.compute_routes origin='{"address":"SF"}' destination='{"address":"LA"}' travelMode=DRIVE

# List tools
mcporter list grounding-lite --schema

Parameters

search_places: 

textQuery
(required), 
locationBias
, 
languageCode
, 
regionCode

lookup_weather: 

location
(required: address/latLng/placeId), 
unitsSystem
, 
date
, 
hour

compute_routes: 

origin
, 
destination
(required), 
travelMode
(DRIVE/WALK)

Notes

  • Rate limits: search_places 100 QPM (1k/day), lookup_weather 300 QPM, compute_routes 300 QPM
  • Include Google Maps links in user-facing output (attribution required)
  • Only use with models that don't train on input data