Google Maps

@google-maps find the top 5 coffee shops within 2km of the Eiffel Tower and show me their ratings and opening hours

Found 5 coffee shops near the Eiffel Tower: (1) Café de l'Homme (4.2★, opens 12pm-11pm daily), (2) Carette (4.4★, opens 7:30am-11pm), (3) Le Café du Trocadéro (3.9★, opens 8am-10pm), (4) Café Kléber (4.1★, opens 7am-midnight), (5) Angelina Paris Rivoli (4.3★, opens 9am-7pm weekdays, 8:30am-7pm weekends). All locations include place IDs for further queries and current operational status. This illustrative example shows typical nearby search results; actual availability and ratings vary by query time.

This example uses the Nearby Search tool to demonstrate location-based discovery. Requires OAuth2 consent for Places API access. Results depend on Google's current place database and may return fewer matches if the radius or type filters are too restrictive. Rate limits apply per project quota.

@google-maps calculate driving time from San Francisco to Los Angeles with a departure at 8am Friday, and compare it to the same trip leaving at 2pm

8am Friday departure: 6 hours 15 minutes (383 miles) via I-5 S, accounting for typical morning traffic clearing by 10am. 2pm Friday departure: 7 hours 45 minutes (same route), with heavy congestion through San Jose and into LA metro area between 4-6pm. The morning departure saves approximately 90 minutes. Distance Matrix also provides fuel cost estimates if enabled. This illustrative comparison shows how departure time affects travel duration; actual conditions depend on real-time traffic data at query time.

This example showcases the Distance Matrix tool's ability to factor departure time into travel calculations. Requires traffic model parameters (best_guess, optimistic, pessimistic) to be specified. Results are estimates based on historical and live traffic patterns, not guarantees. API quota consumed per origin-destination pair.

@google-maps generate turn-by-turn directions from Boston Common to Harvard Square via MIT, then create an embeddable map I can drop into our team wiki

Route generated: (1) Head northwest on Tremont St toward Park St (0.2 mi), (2) Turn right onto Cambridge St (1.1 mi), (3) Continue to Massachusetts Ave toward MIT (2.3 mi), (4) Turn left onto Memorial Drive, destination on right (1.8 mi). Total: 5.4 miles, ~18 minutes by car. Embed code: `<iframe src="https://www.google.com/maps/embed/v1/directions?origin=Boston+Common&destination=Harvard+Square&waypoints=MIT&key=YOUR_KEY" width="600" height="450"></iframe>`. This illustrative output combines routing with embed generation; actual HTML requires your API key substitution.

This example pairs Get Directions with Embed Google Map to show multi-tool workflows. The embed tool generates static HTML that works without JavaScript, ideal for documentation sites. Waypoints are limited to 25 per request. Embedding requires a valid API key with Maps Embed API enabled, separate from the MCP's OAuth2 scope.

When Google Maps MCP handles same-day dispatch scheduling

A 6-person HVAC dispatch team runs morning routing calls where they assign 15-20 service tickets across three techs. The Distance Matrix tool calculates drive times between every job pair in under two seconds, and Get Route returns turn-by-turn sequences the dispatcher pastes into the tech's chat thread. This works cleanly when your service area fits in a single metro region and ticket addresses are already validated—Google's geocoder chokes on apartment unit numbers or rural route boxes about 8% of the time, so you'll manually fix a couple addresses per batch. If your team dispatches more than 40 jobs daily or optimizes across multiple service windows, you need a dedicated routing engine; this MCP is the right call for straightforward same-day sequencing where a human still eyeballs the final route order.

Why this MCP speeds up 'where is my delivery' tickets

A 4-person e-commerce support team fields 30-50 'package not delivered' tickets daily, and half require checking whether the carrier's GPS drop matches the customer's address. The Geocoding tool converts the customer's address and the carrier's lat-long into comparable coordinates in one API call, and Reverse Geocoding confirms the drop point's street name when the coordinates land 200 feet away at a neighbor's porch. This cuts a 90-second Google search down to 12 seconds and eliminates the copy-paste errors that happen when agents toggle between Zendesk and a browser tab. The OAuth2 setup takes 20 minutes the first time—your IT admin creates the Google Cloud project and drops the credentials into Switchy—but after that it's zero-touch. If your support volume is under 100 location checks per day, this MCP is faster than building a custom integration.

When Nearby Search beats manual prospecting lists

A 3-rep sales team covering the Pacific Northwest spends Monday mornings building weekly prospect lists by searching 'dental practices within 15 miles of Seattle' and similar queries for each territory. The Nearby Search tool returns 20 results per query with phone numbers and addresses already formatted, and the Text Search tool handles multi-keyword queries like 'urgent care open Sundays Portland' without the rep needing to learn Google's place-type taxonomy. This replaces 45 minutes of browser tabs and spreadsheet copy-paste with a 6-minute AI conversation that outputs a CSV the reps import into their CRM. The tool count is low—7 total—so there's no decision fatigue about which endpoint to call, and the OAuth2 token refresh happens automatically after the first login. If your territories shift weekly or you prospect more than 100 locations per session, this MCP keeps your list-building inside the same workspace where you draft outreach emails.