Google Maps MCP Server
MCP ServerFreeAccess Google Maps geocoding, directions, and place data via MCP.
Capabilities9 decomposed
geocoding and reverse geocoding with address-to-coordinates mapping
Medium confidenceConverts human-readable addresses to geographic coordinates (latitude/longitude) and vice versa using Google Maps Geocoding API. The MCP server wraps the Google Maps Platform API client, handling request serialization, response parsing, and error handling through the MCP tool interface. Supports batch geocoding operations and returns structured location data including formatted addresses, place types, and geometry bounds.
Exposes Google's authoritative geocoding engine through MCP's standardized tool interface, enabling LLM agents to resolve addresses without custom API integration code. Uses Google's proprietary address parsing and normalization logic that handles 190+ countries and regional address formats.
More accurate than open-source geocoders (OpenStreetMap/Nominatim) for addresses in developed regions, and integrates directly into MCP workflows without requiring separate HTTP client setup
route planning and directions with multi-waypoint support
Medium confidenceComputes optimal routes between origin and destination points using Google Maps Directions API, supporting multiple waypoints, travel modes (driving, walking, transit, bicycling), and real-time traffic conditions. The MCP server translates route requests into Directions API calls, parsing polyline-encoded paths and turn-by-turn instructions into structured JSON responses. Handles mode-specific constraints like transit schedules and toll road preferences.
Integrates Google's real-time traffic-aware routing engine into MCP, enabling LLM agents to make routing decisions based on live conditions. Supports all four travel modes (driving, transit, walking, bicycling) with mode-specific constraints and preferences in a single tool interface.
Includes real-time traffic data and transit schedules that open-source routers (OSRM, Vroom) lack; more accurate than simple distance-based routing for multi-modal trip planning
place search and discovery with text and nearby queries
Medium confidenceSearches for places (businesses, landmarks, geographic features) using Google Maps Places API, supporting both text-based queries and proximity-based nearby searches. The MCP server translates search parameters (query string, location bias, radius, place types) into Places API requests, returning paginated results with place names, types, ratings, and opening hours. Handles ranking by relevance or distance and filters by place type categories.
Exposes both text-based and proximity-based place search through a unified MCP interface, allowing LLM agents to switch between relevance-ranked and distance-ranked results. Integrates Google's massive place database (millions of businesses and landmarks) with real-time ratings and hours.
More comprehensive place coverage than OpenStreetMap for businesses and amenities; includes real-time ratings and hours that OSM lacks; better ranking algorithms for relevance-based searches
place details retrieval with rich metadata extraction
Medium confidenceFetches comprehensive details for a specific place using Google Maps Place Details API, given a place ID or reference. Returns structured metadata including full address, phone number, website, opening hours, photos, reviews, and business attributes. The MCP server handles place ID resolution, field masking for selective data retrieval, and parsing of complex nested structures (hours arrays, review objects, photo references).
Provides field-maskable access to Google's rich place metadata, enabling agents to request only needed fields and reduce API costs. Handles complex nested structures (hours arrays with day-specific times, review objects with author details) and real-time business status.
More complete metadata than Places API text search results; includes photos, reviews, and business attributes that require separate API calls in competing services; field masking reduces costs vs always-full responses
elevation data retrieval for terrain analysis
Medium confidenceQueries Google Maps Elevation API to retrieve elevation (altitude) data for specified locations or along a path. The MCP server translates location coordinates into elevation queries, returning elevation in meters above sea level. Supports both point elevation lookups and path-based elevation profiles for analyzing terrain along routes.
Integrates Google's global elevation dataset into MCP, enabling agents to incorporate terrain analysis into route planning and activity recommendations. Supports both point and path-based elevation queries with consistent accuracy across 190+ countries.
More accurate and globally consistent than SRTM or ASTER elevation data; includes elevation for urban areas and islands; integrated into same API key as other Maps services
distance matrix computation for multi-location analysis
Medium confidenceCalculates travel distances and durations between multiple origin-destination pairs using Google Maps Distance Matrix API. The MCP server batches location pairs into matrix requests, supporting multiple travel modes and returning a structured distance/duration matrix. Handles real-time traffic conditions and can compute distances for up to 625 origin-destination pairs per request.
Enables batch distance computation for up to 625 origin-destination pairs in a single API call, allowing agents to analyze multi-location scenarios efficiently. Integrates real-time traffic and supports all four travel modes with consistent response structure.
More efficient than sequential directions API calls for multi-location analysis; includes real-time traffic that open-source distance APIs lack; supports larger batch sizes than most competing services
mcp protocol integration and tool schema exposure
Medium confidenceImplements the Model Context Protocol (MCP) server specification, exposing all Google Maps capabilities as standardized MCP tools with JSON schema definitions. The server handles MCP transport (stdio or HTTP), tool registration, request routing, and response serialization according to MCP primitives. Each tool is defined with input/output schemas, descriptions, and error handling that enables LLM clients to understand and invoke capabilities without custom integration code.
Official MCP server implementation from Anthropic, ensuring protocol compliance and best-practice patterns. Demonstrates MCP tool registration, schema definition, and error handling as a reference implementation for other server developers.
Eliminates custom API client code in agent logic; standardized schema enables LLM clients to understand capabilities without documentation; official implementation ensures protocol compatibility
api key management and authentication handling
Medium confidenceManages Google Maps Platform API key configuration and authentication for all API requests. The MCP server accepts API key via environment variables or configuration, applies it to all outbound requests, and handles authentication errors gracefully. Supports API key validation and provides clear error messages when credentials are missing or invalid.
Handles API key management transparently, allowing agents to invoke Google Maps tools without managing credentials directly. Supports environment-based configuration for secure deployment in containerized and cloud environments.
Simpler than custom API client setup; integrates authentication into MCP protocol layer so agents never see credentials; supports standard deployment patterns (environment variables, secrets managers)
error handling and api response normalization
Medium confidenceTranslates Google Maps API errors and responses into consistent MCP error and result formats. The server catches API failures (rate limits, invalid requests, service errors), maps them to appropriate MCP error codes, and provides normalized error messages. Handles partial failures in batch operations and returns structured error details that enable agents to implement retry logic or fallback strategies.
Normalizes Google Maps API errors into MCP error format, providing agents with consistent error semantics across all tools. Distinguishes between retryable and permanent failures, enabling intelligent error recovery.
More consistent error handling than raw API client usage; MCP error format enables standardized agent error handling across multiple tools; clearer error messages than raw HTTP status codes
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
Related Artifactssharing capabilities
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Mapbox
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** - Location services, directions, and place details.
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Best For
- ✓LLM agents building location-aware applications
- ✓Chatbots that need to resolve user-provided addresses to coordinates
- ✓Teams building multi-step workflows that require address validation before mapping operations
- ✓Delivery and logistics agents optimizing multi-stop routes
- ✓Travel planning assistants comparing transportation options
- ✓Navigation bots providing real-time directions to users
- ✓Agents analyzing commute feasibility across different travel modes
- ✓Travel and local discovery agents helping users find nearby amenities
Known Limitations
- ⚠Rate-limited by Google Maps Platform quotas (default 50 QPS for standard tier)
- ⚠Geocoding accuracy varies by region; some addresses may return multiple candidates requiring disambiguation
- ⚠Reverse geocoding may return approximate addresses for coordinates in rural or unmapped areas
- ⚠Batch operations not natively supported — requires sequential tool calls for multiple addresses
- ⚠Real-time traffic data only available in supported regions; historical traffic patterns used elsewhere
- ⚠Polyline decoding adds ~50ms latency per route; high-precision paths require additional processing
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
About
Official MCP server for Google Maps Platform APIs. Exposes geocoding, directions, place search, place details, elevation, and distance matrix tools for location-based AI applications.
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