Phase 0 — Strategy & compliance guardrails (1–2 weeks)

Decide what the app should win at in-chat. Discovery is model-driven: ChatGPT calls your app when your tool metadata and use-case language align with the user’s prompt. Start by enumerating high-intent tasks and outcomes.

Define success & constraints

• Target surface: ChatGPT app (Apps SDK) vs. internal use with MCP connectors (workspace-published; write actions gated with confirmations/RBAC in Business/Enterprise/Edu).
• Audience & rollout: Apps visible “today” to logged-in users outside the EU/CH/UK; EU support “soon.”
• Timeline reality: Apps SDK is preview; app submissions open later this year; directory + monetization also slated for later this year.

Deliverables

• Use-case brief, KPI targets, geos/plans, privacy posture aligned to App Developer Guidelines and Security & Privacy (least privilege, explicit consent, write-action confirmations).

Go/No-Go

• Clear problem/app fit in chat, permissible data flows, and submission-ready intent.

Phase 1 — Contract-first POC in Developer Mode (2–3 weeks)

MCP server & tools. Design narrow, single-purpose tool schemas (inputs/outputs) that map directly to tasks (e.g., create_quote, lookup_inventory). This is the foundation the model uses to call you.

Native UI components. Build a minimal, task-focused component that renders inline in chat (use fullscreen only to deepen engagement). Components run in a sandboxed iframe and talk to ChatGPT via window.openai.

Wire into ChatGPT (Developer Mode).

• Host your MCP endpoint over HTTPS (ngrok/Cloudflare Tunnel for local).
• Settings → Apps & Connectors → Create a connector; test prompts end-to-end.

Testing loop. Use MCP Inspector and API Playground to inspect tool calls, schemas, and component rendering before UI polish.

Security basics. Enforce server-side validation; mark write actions so ChatGPT inserts confirmation modals; plan OAuth 2.1 + PKCE if your app links user accounts.

Exit criteria

• Golden prompts reliably select your tool and pass correct args; no console errors; write actions require confirmation.

Phase 2 — Alpha with real data & auth (2–4 weeks)

Authenticate users. Introduce sign-in/consent only when needed (customer data or writes). Follow OAuth 2.1 with PKCE; verify scopes per tool call.

Optimize discovery. Tighten names, descriptions, and parameter docs—ChatGPT uses your metadata to decide when to invoke your app. Iterate copy as product, not afterthought.

Accessibility & mobile. Test layouts on ChatGPT web and mobile; keep tasks short, inputs minimal, and use fullscreen sparingly.

Exit criteria

• Auth flows stable; discovery recall/precision measured on a curated prompt set; PII-redacted logs and retention policy documented.

Phase 3 — Beta hardening & submission readiness (2–3 weeks)

Policy compliance (submission-level).

• Privacy policy published; data minimization; no PCI/PHI/IDs/API keys/passwords; accurate action labels for writes; clear support contact; verified developer.

Reliability. Apps “submitted as betas/trials” or that crash/hang will be rejected—stabilize latency, error handling, and structured outputs.

Regression suite. Re-run MCP Inspector + Developer Mode tests; capture screenshots and payloads as launch evidence.

Exit criteria

• All App Developer Guidelines controls mapped; security checklist from the Security & Privacy guide satisfied (least privilege, consent, CSP sandbox, logging).

Phase 4 — Distribution prep (when submissions open later this year)

Submission package. Final metadata (name, description, screenshots), clear tool descriptions, demo credentials if auth is required. Tool titles/definitions lock post-listing; changes require re-submission.

Directory & monetization. Prepare variants for upcoming app directory and monetization, with optional Agentic Commerce Protocol (ACP) for Instant Checkout if you sell directly in ChatGPT.

Go-to-market. Target top intents (e.g., “create quote”, “book demo”) so your app is suggested contextually; align marketing with the phrasing users will type.

Phase 5 — Post-launch operations & growth

Observability. Track tool call success, confirmation rates on write actions, abandonment after UI render, and prompt patterns that miss discovery; iterate metadata and schemas.

Governance & updates. To change tools or signatures after listing, plan a re-submission; keep dependencies patched and monitor for prompt-injection attempts as part of routine QA.

Enterprise channel (optional). For internal deployments, publish MCP connectors to the workspace with admin controls and RBAC (Enterprise/Edu). Write actions will always prompt for explicit confirmation.

Milestone checklist (printable)

A. Product fit & discovery

• Use-case map with the exact language buyers type → passes discovery tests.

B. Technical readiness

• MCP server exposes narrow JSON-schema tools; components render inline; fullscreen only when it deepens engagement; Developer Mode E2E tested.

C. Security & privacy

• Least privilege scopes; consent & confirmations for writes; PII-redacted logs; retention policy published.

D. Compliance for submission

• Preview status acknowledged; submissions later this year; developer verification, support contact, sensitive data bans met.

E. Distribution

• Directory assets ready; ACP considered if you need Instant Checkout.

Why work with us

We ship contract-first MCP backends, native in-chat UI, and a submission-ready privacy & permissions posture—tested with MCP Inspector and Developer Mode—so you’re ready when the directory and monetization open later this year. Every milestone above maps 1:1 to OpenAI’s own docs and help-center guidance.