# Extensions (now "Apps"): connecting Gemini to Google services
Ask Gemini "summarize the key points from this YouTube video" and paste a link, and it will actually read the transcript and answer, no copy-paste required. That single move (reaching out to a live Google service to get real data) is what the app's connectors do. They turn Gemini from something that talks about the world into something that can pull from it.
> Naming note: Google has been retiring the "Extensions" label in the Gemini app and now calls these connectors Apps (sometimes "connected apps"). You will still see the older "Extensions" wording in some places and in older docs. The behavior is the same: a connector that lets Gemini reachreachThe number of unique people exposed to your message in a given period. Unlike impressions, reach counts each person once, no matter how often they see it.Voir la définition complète → a named Google service in real time. This lesson uses "Apps" for the current UI and notes where the old term still appears.
An App (formerly Extension) is a connector that lets the Gemini app call a specific service on your behalf, in real time, inside a normal conversation. When a connector is on and your prompt clearly needs it, Gemini routes part of the request to that service, gets structured data back, and weaves it into the answer.
The Google-built connectors available in the Gemini app include:
This is different from grounding with Google Search, which fetches public web results to reduce hallucinationhallucinationA hallucination is when an AI model generates output that is fluent and confident but factually wrong, fabricated, or unsupported by its source data.Voir la définition complète →. Apps reachreachThe number of unique people exposed to your message in a given period. Unlike impressions, reach counts each person once, no matter how often they see it.Voir la définition complète → into *named services* (often your private data, like your own Drive) and can return service-specific structure. Search grounding answers "what is true on the open web." Apps answer "what is in this video / my Drive / this route."
> Note: connector names and availability shift over time and by account type. The current list lives in the Gemini Apps Help Center, which is the source of truth.
Say you saved a conference talk to "watch later" and also have a strategy doc in Drive. You want both reconciled.
Prompt:
> Summarize the 5 main arguments in this talk: youtube.com/watch?v=EXAMPLE, then find my Drive doc named "2026 Roadmap" and tell me which arguments contradict our plan.
Here is what happens under the hood:
1. Gemini detects two intents: a YouTube lookup and a Drive lookup.
2. The @YouTube connector fetches the video's transcript and metadatametadataDonnées sur les données, informations décrivant le contexte, la structure, la provenance et les caractéristiques d'un asset de données (auteur, date, format, source, définition)..
3. The @Google Workspace connector searches *your* Drive for the file "2026 Roadmap."
4. Gemini fuses both sources and produces the comparison.
You can force a tool explicitly by typing @ in the Gemini app, which opens the picker. @YouTube summarize this: <link> is unambiguous and tends to be more reliable than hoping Gemini infers it.
One real constraint worth internalizing: the Workspace connector searches content *you already own and can access*. It is bounded by your Google account permissions. It will not surface a colleague's private file you cannot open. This is the security model, not a limitation to work around.
These connectors are managed per account, not per chat.
1. Open the Gemini app.
2. Go to Settings → Apps (older builds may still label this Extensions).
3. Toggle each one (YouTube, Workspace, Maps, Flights, Hotels) on or off.
When you enable the Workspace connector the first time, you grant Gemini permission to read your Gmail, Drive, and Docs content for the purpose of answering your prompts. You can revoke this at any time from the same panel or from your Google Account permissions page.
Two things that trip people up:
@Gmail returns nothing, check with your Workspace admin before assuming it is broken.Gemini Extensions explained
The Gemini *app* connectors above are pre-built, consumer-facing, and managed with toggles. But the real depth for a builder is that the *same idea* (let the model call live tools) is something you implement yourself through the APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète →. Knowing where the line sits matters.
A Gem (your saved custom assistant) operates inside the Gemini app, so it inherits the connectors you have enabled. A "Travel Planner" Gem can lean on Maps and Flights without you re-enabling anything per chat. The Gem's instructions shape *how* it uses them; the account toggle controls *whether* they exist.
When you move to Google AI Studio and the Gemini APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète →, you do not get the app's pre-built YouTube or Drive connectors. Instead you wire up capabilities yourself. Two mechanisms matter:
1. Built-in tools. The APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète → exposes first-party tools you switch on, most notably grounding with Google Search and code execution. This is config, not custom code:
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-2.5-flash",
contents="What were Google's most recent AI announcements?",
config=types.GenerateContentConfig(
tools=[types.Tool(google_search=types.GoogleSearch())]
),
)
print(response.text)That google_search tool is the APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète → equivalent of the app's search grounding: the model decides when to query, fetches live results, and cites them. You read the model tier from the model string. Flash is the fast, cheaper tier for high-volume tool calls; Pro is the stronger reasoner for complex multi-step tool use.
2. Function calling (your own tools). This is how you connect Gemini to *any* app or APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète → you control: your CRMCRMCustomer Relationship Management: software and strategy to manage and analyse customer interactions throughout their lifecycle.Voir la définition complète →, an internal inventory service, a payments system. You describe a function; the model decides when to call it and with what arguments; your code runs it and returns the result.
from google import genai
from google.genai import types
def get_order_status(order_id: str) -> dict:
# Your real backend call goes here.
return {"order_id": order_id, "status": "shipped", "eta": "2026-03-14"}
client = genai.Client()
chat = client.chats.create(
model="gemini-2.5-flash",
config=types.GenerateContentConfig(tools=[get_order_status]),
)
reply = chat.send_message("Where is order A-2291?")
print(reply.text)The SDK reads your function's signature and docstring to build the tool schemaschemaA schema is the formal blueprint that defines how data is structured, named, typed, and related within a database, file, or message.Voir la définition complète → automatically, calls get_order_status("A-2291") when needed, and feeds the result back into the conversation. *This* is the building block behind every "Gemini that does things" you will ship. The app's Maps connector is just a polished, hosted version of the same pattern.
Vérification des acquis
1. What best describes the core purpose of an Extension in the Gemini app?
2. How does using Extensions fundamentally differ from grounding with Google Search?
3. In the example prompt combining a YouTube link and a Drive doc, why does Gemini invoke two different extensions?
4. Select ALL statements that correctly describe how Extensions behave in the Gemini app.
Sélectionnez toutes les réponses correctes.
5. Select ALL reasons why explicitly typing something like '@YouTube summarize this: <link>' can be preferable.
Sélectionnez toutes les réponses correctes.
Function calling is one tool, one turn. Real systems need many tools, memory, and multi-step planning. Google's stack gives you escalating options.
If your "app" *is* Google Workspace (a Sheet that should email a summary, a Doc that triggers a workflow), Apps Script lets you call the Gemini APIAPIApplication Programming Interface: a standardised interface that lets applications communicate and exchange data without knowing each other's internal workings.Voir la définition complète → from inside the Workspace environment with a UrlFetchApp request or the Vertex AI integration. This is the lowest-friction way to give a spreadsheet live AI behavior without standing up servers.
The Agent Development Kit is Google's open-source framework for building agents that orchestrate multiple tools, maintain state across steps, and can hand off to other agents. Where function calling is "model calls one function," ADK is "agent runs a plan that may call ten functions, retry, and delegate." If you are building the production version of a multi-tool assistant, ADK is the structured way to do it.
Ces actions sont compilées dans le plan d'action du rôle.
Two more "connectors in spirit" worth naming. Gemini CLI brings the model into your terminal so it can read your filesystem, run commands, and act on a local project. Gemini Code Assist embeds it in your IDE. Both are tool-using Gemini connected to a developer's working environment rather than to consumer apps, and both are useful when the "live data" you want Gemini to reachreachThe number of unique people exposed to your message in a given period. Unlike impressions, reach counts each person once, no matter how often they see it.Voir la définition complète → is your own codebase.
A quick decision guide:
@).The through-line: every one of these is the same core capability (a model that can decide to call a tool and use the result), exposed at a different altitude. Learn it once at the app level, recognize it everywhere else.
@YouTube, @Gmail, or @Maps explicitly when you need service-specific or private data; use search grounding for fresh public facts.@ picker.@Gmail or @Drive returns nothing.