Gemini Connected Apps: a new MCP growth channel
Gemini Connected Apps let an MCP server work inside the Gemini app and Google Search, and on October 28, 2026 Google opened the program to more developers with the Connected Apps Platform. For a team that ships an MCP server, that is a new distribution channel run by the company behind Google Search. This article covers what Connected Apps are, how Gemini users reach them, why Google’s search history makes the channel familiar, what Google reviews, and how to measure what the channel brings you once you are listed.
Key takeaways
- The Connected Apps Platform brings third-party apps into the Gemini app and Search. You connect through a remote MCP server (or Android MCP via AppFunctions) and register it in the Google Connected Console.
- Google says it has launched more than 50 Connected Apps, Adobe, Experian, Localiza and Peloton among them. The platform is in preview, and access opens in phases.
- Users @mention an app by name or add it from a list, and Gemini picks tools by matching the request against your tool schemas. Your names and descriptions do the work that titles and snippets do in Search.
- Google’s policy bans tool descriptions written to make the model prefer your app. In my view, prompt injection is the reason reviews of this kind are strict.
- Test before you submit: MCP Tower checks your OAuth sign-in and validates your tools and their descriptions.
- The Google Connected Console reports traffic, latency and error rates for Google’s products. To compare Gemini with ChatGPT, Claude and other agents, you need your own MCP analytics.
What are Gemini Connected Apps?
A Connected App is a third-party service that a user links once to their Google account and then uses from Google’s AI products. Google’s announcement calls the Connected Apps Platform “a unified way for more app developers to bring their capabilities directly into Gemini and Search.” A developer builds the integration, then registers, tests and submits it in the Google Connected Console.
There are two ways in. An Android app can expose functions on the device with AppFunctions. Everyone else connects a remote MCP server, and that is the path this article is about. Google’s MCP server guide asks for a public HTTPS endpoint, and its OAuth 2.1 guide covers account linking for servers that act on a user’s account.
The names differ from assistant to assistant. Google says “Connected Apps”, ChatGPT says “plugins”, and Claude, Muse and Perplexity say “connectors”. Under each name sits the same thing: a reviewed remote MCP server that the assistant can call for the user.
How Gemini users find and use a Connected App
On gemini.google.com, Google’s Gemini help page
describes two ways in. Users browse: Customize, then Connectors, lists the apps available to
them, each with a description, supported actions and example prompts, and Add connects one. Or
they type @ and the app’s name in the prompt. If that app is not connected yet, Gemini connects it
or asks for permission first.
Once a request reaches the platform, Google’s MCP flow says it “analyzes a user’s query” and checks the available tool schemas to find the right tools. The server optimization guide adds that a tool’s description is the only context the model has to decide whether the tool fits.
Google’s listing rules show which of these paths it expects. The
prerequisites ask for at least
three example prompts. At least two must start with the app’s name, and at least one must mention it
in the middle of a sentence. The name you register is the one users type after @. So your brand
name works like a navigational query in Search: the people who already know you ask for you by name,
and your tool descriptions decide which tool Gemini calls for them.
Why Gemini Connected Apps are a new MCP distribution channel
Most software reaches users through search, ads or word of mouth. A Connected App can also reach them through the assistant, in the middle of a conversation, when they ask for something your server does. Google’s own pages add three reasons to plan for this channel:
- One registration covers two products. In the console you choose where each version is available by country or region, language and Google product, and Google’s announcement names the Gemini app and Search.
- The users are already there. You do not build an audience for the Gemini app; you get in front of the one it has.
- The quality bar favors real services. Google’s quality guidelines ask for live data, personal context or completed actions: an app that “gets better when the user signs in”, or one that lets users create, book, order or update things they cannot do in Google’s products today.
The same guidelines list what does not qualify. Moving read-only data behind a tool call is “a transport change, not a connected app”, and for broad discovery Google says a data feed is still the best way. Generic content that needs no account, and adds nothing to what Gemini or Search can already answer, does not qualify either. A server that holds user accounts, inventory, bookings or anything else users act on fits the channel. One that repackages public data does not, by Google’s own rules.
Google Gemini apps and the lessons of SEO
Search has always worked from what site owners write about their pages: Google matches it to what people ask and demotes owners who write for the ranking instead of the reader. Its spam policies name the old tricks, keyword stuffing and cloaking among them.
The Connected Apps policy reads like the same rulebook, rewritten for tools. It forbids “overly broad or deceptive capability descriptions” used to influence the model, and it names cloaking and obfuscation used to hide an app’s behavior. The server optimization guide goes further and bans “any kind of SEO prompt that instructs the model to prefer your tool over similar ones”, along with descriptions that name other apps’ tools.
In Search, the pages that lasted were the ones that answered the query well. I expect the same
for Gemini MCP apps: the tools that get called will be the ones whose names and descriptions say
plainly what they do, so the model can match them to a request. Google’s guide is specific: use
verb_noun names like publish_draft, keep one purpose per tool, state formats and units, and
describe what the tool returns.
Gemini MCP apps vs ChatGPT and Claude
Each assistant shapes discovery differently, and the differences decide what you write.
| Gemini Connected Apps | ChatGPT plugin directory | Claude connectors directory | |
|---|---|---|---|
| Where users find apps | Customize, then Connectors; @ mentions | Direct link or search by name | Customize, then Connectors; in-chat suggestions |
| Where it runs | Gemini app and Search | ChatGPT and Codex | claude.ai, Desktop, mobile, Claude Code, Cowork |
| What you describe | Capabilities and example prompts with name | Five positive and three negative test cases | Use cases and example prompts |
| Built-in analytics | Traffic, latency and error rates | None | Health, tool calls, error rate, usage by tool |
The ChatGPT side is covered in why the ChatGPT plugin directory can be a growth channel, and the Claude side, including how Claude suggests connectors mid-chat, in why the Claude Marketplace can be a growth channel.
Why the review is strict, and how to pass it
Google’s policy does not use the words “prompt injection”, but much of it is about that risk. Apps must not “deceive or influence the model into performing an adverse action or behavior”, must not return system instructions in their responses, and must not set rules for how other tools are used. In my view, prompt injection is the main reason every directory reviews MCP servers this carefully: a tool description goes straight into the model’s context, and a malicious one can steer every conversation where the app is active. Gemini adds server instructions to its system prompt, which raises the stakes further.
That is where MCP Tower comes in first, before you submit. Its Inspect module validates your tools and their descriptions and gives recommendations: missing titles or annotations, catch-all tools, and descriptions that read like orders to the model instead of a plain account of what the tool does. Inspect also lets you change tool titles and descriptions yourself through overrides, without waiting for your developers. For Gemini, make those changes before you sync tools in the console. Google snapshots your tools when you register a version, and changing them on a live version can get the app disabled.
Test sign-in as well. A reviewer who cannot link an account cannot test a single tool, and broken authentication delays review. MCP Tower signs in to your server the way agents do and runs each step as a check, from discovery documents and PKCE to token exchange and refresh, then reports where the flow broke and what to change.
The full submission, step by step, is in how to submit an app to Gemini.
Measure Gemini traffic like an SEO specialist
Google gave site owners Search Console, and Connected Apps get a smaller version of it. After launch, the Google Connected Console lets you “track traffic, latency, and error rates”, per Google’s announcement. Those numbers cover Google’s products only, so they cannot tell you how Gemini compares with ChatGPT, Claude or Cursor, and the docs describe no report of the links users open from your results.
An SEO specialist would not run a site on one search engine’s console alone. MCP Tower is the first
product built to show how AI agents use an MCP server, and it is the second reason to set it up
before you submit. It is a hosted proxy: you publish its URL on your own hostname instead of your
server’s, and every request passes through to your server while MCP Tower records what happened. You
need no SDK and no code change. Google documents that Gemini sends User-Agent: Google on its MCP
requests and suggests using it for analytics; MCP Tower records the agent signals of every call,
including the user agent.
What you get:
- Tool calls from every AI agent on one chart, so you can compare what each listing brings.
- Usage and reliability per tool: which tools are called, how often, how fast and with which errors, filtered by agent, country and date.
- What happens after the call: clicks on the links your tools return and interactions inside widgets, so you can follow a call to a visit on your site.
- Uptime checks on a schedule, whether or not anyone is using your server.
Because the listing points at the endpoint you register, put MCP Tower in front of the server before you connect it in the console. Your first day of Gemini traffic is then already measured. See pricing for plans.
Conclusion
Gemini Connected Apps turn a remote MCP server into something Gemini and Search users can @mention, connect and use mid-conversation. Google runs it with the habits of Search: clear descriptions get matched, manipulation breaks policy, and the console reports the basics. The teams that get the most from it will test sign-in and tool descriptions before they submit, then watch what agents do once the app is live and adjust.
Get started with MCP Tower to test your MCP server before you submit to Gemini, then see which AI agents use it from the first call.
