Build with Google AI Studio
Google AI Studio can turn a business brief into a working web or Android experience, show it in a live preview, and help you publish it. Inttegro MCP can prepare the integration plan; the finished app then performs live Inttegro work through a protected server.
Open Google AI Studio · Read the Google AI Studio documentation
Google documents external MCP tools for the Agents playground, while app creation happens in Build mode. Use the agent to produce an Inttegro-aware plan, then give that approved plan to Build mode. The published app must call the Inttegro API from server code—it does not inherit the agent's MCP access.
Plan with Inttegro MCP
- Open the Playground in Google AI Studio and switch to Agents.
- In the agent's tool configuration, connect the Inttegro MCP server at
https://mcp.inttegro.comusing the least privilege available. - Keep write operations subject to human approval and test with disposable Inttegro data.
- Ask the agent to call
design_integration, review the returned plan, and carry only the approved brief into Build mode.
Google's Agents playground guidance covers external MCP tools, least privilege, test data, and human oversight.
Paste this into Build mode
Open Google AI Studio Build mode and start with the approved plan from the previous step. If you skipped the Agents playground, add links to the relevant Inttegro Studio operation pages so Gemini has the exact contracts rather than asking it to guess.
Business outcome
Build [describe what a customer or team member should be able to accomplish] for [describe the business and its users]. Make it feel native to the business, and preserve any existing visual language, authentication, and data.
Understand the experience before changing it
- Read the approved Inttegro integration plan and inspect every current file, screen, user flow, data source, and server boundary that it affects.
- Ask me one concise round of questions for unresolved business decisions. Do not ask me to paste an Inttegro credential into the prompt.
- Show me the recommended journey, the Inttegro operations it uses, what data stays in this app, failure and recovery states, and a definition of done. Wait for approval before building.
Build the approved journey
- For a web app, put every live Inttegro call in AI Studio's server-side runtime. Browser code may call that boundary but must never receive the Inttegro credential.
- Add
INTTEGRO_API_KEYthrough Settings → Secrets and read it only in server code. Never put it in browser code, a prompt, source control, logs, or an error response. - Inspect the actual server runtime before choosing a client. Use the official Inttegro TypeScript SDK only when the runtime satisfies its documented Node.js requirement; otherwise make exact server-side HTTPS calls from the Studio operation references.
- For an Android app, never put
INTTEGRO_API_KEYin the APK. Use a separate authenticated backend for privileged Inttegro work and expose only the narrow actions the mobile experience needs. - Validate and authorize browser or mobile input at the server boundary. Use a stable idempotency key for every mutation, and look up the authoritative resource after redirects, timeouts, or uncertain results.
- Build complete loading, success, empty, retryable-error, and terminal-error states. Do not copy Inttegro resources into local storage without a specific business reason.
Verify and publish
Run the project's checks and check_integration_readiness. Exercise the full
happy path and one safe failure path in Preview at mobile and desktop sizes.
Inspect generated code and browser traffic for accidental client-side Inttegro
calls. Fix failures before publishing, then report the server files changed,
the single secret I must configure, test evidence, and the one action I should
take next.
What Google AI Studio should create
- one obvious journey from the user's intent to a confirmed outcome;
- a narrow, authenticated server action for each Inttegro workflow;
- protected secret access in server code only;
- stable idempotency and authoritative recovery after uncertain results;
- useful feedback for every waiting, success, and failure state; and
- a reviewed project that can be synchronized to GitHub or published.
Google's server and secrets guide describes the protected runtime, third-party credentials, and external API calls available to Build mode.
Choose the right publishing path
For a web experience, AI Studio can publish the app to a managed Cloud Run service. Review the generated code, configure the required secret, and verify the deployed browser traffic before sharing the URL. The official deployment guide explains the available publishing tiers and URLs.
If you connect GitHub, treat the repository as the durable record: review the diff, run the same checks outside the preview, and merge through your normal review process. For Android, keep privileged Inttegro operations on the separate backend even when the generated client is ready for device testing.