Starting today, developers will be able to use the Google Maps tool in the Gemini API to ground their apps in the rich and up-to-date geospatial data.Today we’re launching the Google Maps tool in the Gemini API, allowing developers to ground their applications in Maps data. This allows developers to connect Gemini's reasoning capabilities with data from more than 250 million places, allowing a new class of powerful, geospatial-aware AI products. Just like Grounding with Google Search, Grounding with Google Maps provides rich, up-to-date data to the model for any query where location information is helpful.
See the feature in action in the demo video below in Google AI Studio. You can check out the app in Google AI Studio and remix it to add additional tools, UI elements and more.
Get started
To get started, enable the Grounding with Google Maps tool in your Gemini API request.
Here is an example using the Python SDK:
from google import genai
from google.genai import types
client = genai.Client()
prompt = "What are the best Italian restaurants within a 15-minute walk from here?"
response = client.models.generate_content(
model='gemini-2.5-flash-lite',
contents=prompt,
config=types.GenerateContentConfig(
tools=[types.Tool(google_maps=types.GoogleMaps())],
# Optionally provide the relevant location context (this is in Los Angeles)
tool_config=types.ToolConfig(retrieval_config=types.RetrievalConfig(
lat_lng=types.LatLng(
latitude=34.050481, longitude=-118.248526))),
),
)
print(response.text)
if grounding := response.candidates[0].grounding_metadata:
if grounding.grounding_chunks:
print("Google Maps sources:")
for chunk in grounding.grounding_chunks:
print(f'- [{chunk.maps.title}]({chunk.maps.uri})')To make it easier to visualize grounded Maps results, you can also use the returned context token to retrieve an interactive widget that you may optionally render in your application UI, giving users a familiar experience complete with relevant photos, reviews and other details.
Improve model responses with grounding data
Developers can use Grounding with Google Maps to create more intuitive and helpful experiences across travel, real estate, retail and logistics. The model automatically detects when a query has geographical context and uses Google Maps data to provide a grounded response. Google Maps uses data from places, and other related content like user reviews, as sources to help generate the response. You can provide latitude and longitude coordinates to localize search results to specific geographic locations.
Here are a few ways you can use this:
Detailed itinerary planning: Go beyond a simple list of places. A travel app can now generate a full day’s plan, complete with distance, travel time and local details. A user could ask, "Plan a day in San Francisco for me. I want to see the Golden Gate Bridge, visit a museum and have a nice dinner," and receive a complete, workable itinerary that includes up-to-date business and holiday hours.
Hyper-local personalized recommendations: Offer tailored recommendations based on your user’s preferences and the location you designate. A real estate app could help a family find rental listings in kid-friendly neighborhoods by identifying nearby playgrounds, schools and parks.
Local place-based answers: Answer detailed questions about a specific location by pulling insights derived from sources like user reviews and other Maps data. A query like, "Does the cafe on the corner of 1st and Main have outdoor seating?" can now receive a Maps grounded answer.
Combine Grounding for Maps and Search
For the most powerful and contextually aware applications, you can enable both Grounding with Google Maps and Grounding with Google Search in the same request.
Google Maps provides grounding with structured, factual data like addresses, hours and user ratings.
Google Search provides descriptive, timely context from across the web, like event schedules, news and articles.
For example, when asked about “live music on Beale Street”, combining tools allows the model to use Maps data for a venue's operating hours and Search data to find the specific start times for evening shows. Internal evaluations show that using both tools together results in a significant improvement in response quality compared to using either alone.