mcp server

Google Maps MCP Server

18 Google Maps tools for AI agents — geocode, search, directions, weather, and more.

Description as published by the maintainer. Source

• version 0.0.53
• active
• retrieval

active — Most recent push to the repository was 2026-07-08. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.

What this server can do

18 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

maps_air_quality(latitude, longitude, includePollutants, includeHealthRecommendations)

Get air quality for a location — AQI index, pollutant concentrations, and health recommendations by demographic group (elderly, children, athletes, pregnant women, etc.). Use when the user asks 'is the air safe', 'should I wear a mask', 'good for outdoor exercise', or is planning travel for someone with respiratory/heart conditions. Coverage: global including Japan (unlike weather). Returns both universal AQI and local index (EPA for US, AEROS for Japan, etc.). Required: latitude, longitude.

maps_batch_geocode(addresses)

Geocode multiple addresses in one call — up to 50 addresses, returns coordinates for each. Use when the user provides a list of addresses and needs all their coordinates, e.g. 'geocode these 10 offices' or 'get coordinates for all these restaurants'. For more than 50, use the CLI batch-geocode command instead. Required: addresses.

maps_compare_places(limit, query, userLocation)

Compare multiple places side-by-side in one call — searches by query, gets details for each result, and optionally calculates distance from your location. Use when the user asks 'which restaurant should I pick', 'compare these hotels', or needs a decision table. Replaces the manual chain of search-places → place-details → distance-matrix. Required: query.

maps_directions(mode, origin, avoid_tolls, destination, arrival_time, avoid_highways, departure_time)

Get step-by-step navigation directions between two points with route details. Use when the user asks 'how do I get from A to B?' and needs the route summary, total distance, estimated travel time, or turn-by-turn instructions. Supports departure/arrival times and multiple travel modes. Required: origin, destination.

maps_distance_matrix(mode, origins, avoid_tolls, destinations, avoid_highways, departure_time)

Calculate travel distances and durations between multiple origins and destinations in a single request. Use for comparing travel options — e.g., 'which hotel is closest to the office?' or batch distance calculations. Supports driving, walking, bicycling, and transit modes. Required: origins, destinations.

maps_elevation(locations)

Get elevation (meters above sea level) for geographic coordinates. Use when the user asks 'how high is this place', 'is this area flood-prone', or needs altitude for hiking/cycling route profiles. Also useful for real estate risk assessment — low elevation near water suggests flood risk. Required: locations.

maps_explore_area(topN, types, radius, location)

Explore what's around a location in one call — searches multiple place types, gets details for the top results, and returns a categorized summary. Use when the user asks 'what's around here', 'explore the area near my hotel', or needs a quick overview of a neighborhood. Replaces the manual chain of geocode → search-nearby → place-details. For trip planning: use search_places first to get geographically spread anchor points, then call this tool around each anchor (e.g. 'Gion, Kyoto') — never pass just the city name, as it clusters all results in one area. After results, call static_map to visualize. Required: location.

maps_geocode(address)

Convert an address, city name, or landmark into GPS coordinates (latitude/longitude). Use when you need coordinates for a location described in text — for example, to provide a center point for search_nearby or a starting point for maps_directions. Required: address.

maps_local_rank_tracker(center, keyword, placeId, gridSize, keywords, gridSpacing)

Track a business's local search ranking across a geographic grid (like LocalFalcon). Searches the same keyword(s) from multiple coordinates around a center point to see how rank varies by location. Supports up to 3 keywords for batch scanning. Returns rank at each grid point, top-3 competitors per point, and summary metrics (ARP, ATRP, SoLV). Useful for local SEO analysis. Required: placeId, center.

maps_place_details(placeId, maxPhotos)

Get comprehensive details for a specific place using its Google Maps place_id. Use after search_nearby or maps_search_places to get full information including reviews, phone number, website, and opening hours. Set maxPhotos (1-10) to include photo URLs — omit or set to 0 for no photos (saves tokens). Required: placeId.

maps_plan_route(mode, stops, optimize, avoid_tolls, avoid_highways, departure_time)

Plan an optimized multi-stop route in one call — geocodes all stops, uses Routes API waypoint optimization (up to 25 intermediate stops) to find the most efficient visit order, and returns directions for each leg. Use when the user says 'visit these 5 places efficiently', 'plan a route through A, B, C', or needs a multi-stop itinerary. Replaces the manual chain of geocode → distance-matrix → directions. For multi-day trips: create one plan_route call per day with stops that follow a geographic arc (e.g. east→west) rather than mixing distant areas. After results, call static_map to visualize the route. Required: stops.

maps_reverse_geocode(latitude, longitude)

Convert GPS coordinates (latitude/longitude) into a human-readable street address. Use when you have coordinates from another tool's output or a user's shared location and need the actual address. Required: latitude, longitude.

maps_search_along_route(mode, origin, textQuery, maxResults, destination)

Search for places along a route between two points — restaurants, cafes, gas stations, etc. ranked by minimal detour time. Use for trip planning to find meals, rest stops, or attractions between landmarks without backtracking. Internally computes the route, then searches along it. Essential for building itineraries where stops should feel 'on the way' rather than 'detour to'. Required: textQuery, origin, destination.

maps_search_nearby(center, radius, keyword, openNow, minRating)

Find places near a specific location by type (e.g., restaurants, cafes, hotels). Use when the user wants to discover what's around a given address or coordinates, such as 'find coffee shops near Times Square' or 'what hotels are near the airport'. Supports filtering by place type, search radius, minimum rating, and whether currently open. Required: center.

maps_search_places(query, openNow, minRating, includedType, locationBias)

Search for places using a free-text query like 'sushi restaurants in Tokyo' or 'best coffee shops near Central Park'. More flexible than search_nearby — supports natural language queries, optional location bias, rating filters, and open-now filtering. Use when the user describes what they're looking for in words rather than by type and coordinates. Required: query.

maps_static_map(path, size, zoom, center, maptype, markers)

Generate a map image with markers, paths, or routes — returned as an inline image the user can see directly in chat. PROACTIVELY call this tool after explore_area, plan_route, search_nearby, or directions to visualize results on a map — don't wait for the user to ask. Use markers from search results and path from route data. Supports roadmap, satellite, terrain, and hybrid views. Max 640x640 pixels.

maps_timezone(latitude, longitude, timestamp)

Get the timezone and current local time for a location. Use when the user asks 'what time is it in Tokyo', needs to coordinate a meeting across timezones, or is planning travel across timezone boundaries. Returns timezone ID, UTC/DST offsets, and computed local time. Required: latitude, longitude.

maps_weather(type, latitude, longitude, forecastDays, forecastHours)

Get weather for a location — current conditions, daily forecast (10 days), or hourly forecast (240 hours). Use when the user asks 'what's the weather in Paris', is planning outdoor activities, or needs to pack for a trip. Coverage: most regions supported, but China, Japan, South Korea, Cuba, Iran, North Korea, Syria are unavailable. Required: latitude, longitude.

Last successful function declaration observed on 2026-08-13. Source: pkg:npm/@cablate/mcp-google-map. We list what the server declared; we do not call any of these functions.

Endpoint status observed on 2026-08-13. Source: pkg:npm/@cablate/mcp-google-map.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Where to get it

• Repository — https://github.com/cablate/mcp-google-map
• npm: @cablate/mcp-google-map

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These share tags the maintainers applied themselves, such as geocoding, places-api, geospatial, agent-skill. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.

This is not a recommendation and not a test result. It is a map of what the authors said their work is about.

How the author describes it

Topics the maintainer set on GitHub: agent-skill, ai, ai-agent, dive, geocoding, geospatial, google-map, google-maps, mcp, mcp-server, model-context-protocol, places-api, streamable-http, typescript.