How to Publish a ChatGPT Connector: Review, Auth, and Distribution

Publishing a ChatGPT connector makes a configured connection available beyond your own account — to teammates, your organization, or users through a broader distribution channel. The core steps are choosing an authentication method, defining the minimum scope, testing with realistic permissions, and completing the required review. Tools like fenbs keep the release checklist and approval decisions in one shared record so everyone on the project starts from the same facts.

The process differs depending on how widely you are distributing. An internal connector shared within your ChatGPT organization skips several review steps. A connector intended for broader distribution goes through a fuller review before it becomes available.

What publishing a ChatGPT connector involves

A connector is a configured link between ChatGPT Work and an external service. Publishing it means deciding who can use that link and making it accessible to them. Before anyone can use it, the connector needs working authentication, an accurate description of what it accesses, and a clearly defined scope of permissions.

For current details on review requirements and submission steps, consult OpenAI's developer documentation↗ (opens in a new tab). Requirements change, and the primary source is more reliable than any summary.

Authentication: OAuth versus API key

Most connectors use one of two authentication approaches. OAuth 2.0 lets each user authorize access with their own account, so each person's access is separate and revocable independently. API key authentication uses a single credential shared across everyone who uses the connector — simpler to set up, but the key controls access for all users at once.

OAuth is the better choice when users have their own accounts in the connected service and when individual access control matters. API keys are reasonable for internal tools where a shared service account is already normal practice.

• OAuth: confirm the redirect URI matches exactly and the requested scopes are limited to what the connector genuinely needs.
• API key: confirm the key is stored as a server-side secret, not embedded in any public-facing file.
• Both: test with a low-privilege account before testing with an admin account — admin credentials can hide permission errors regular users will encounter.
• Both: confirm that revoking the credential from the connected service immediately blocks the connector.

Scope: request only what the connector needs

Define the scope before you write the connector spec. List what the connector reads, what it writes, and what it deliberately does not touch. Reviewers check whether the requested permissions match the stated purpose, and users see the scope at the consent screen.

Overly broad permissions are one of the most common reasons a connector fails review or loses user trust. If the connector reads calendar events, it does not need permission to send emails. Keep the scope to the minimum needed for the stated job, and document the reasoning.

Distribution: internal versus broader release

Internal distribution lets you share a connector with members of your ChatGPT organization through your organization settings. You choose which members or groups can see it, and the connector does not go through a public review queue. This is appropriate for connectors that access internal company systems.

Broader distribution sends the connector through a review process that checks safety, accuracy of the description, working authentication, and compliance with usage policies. Allow time between submission and your planned release date. Check OpenAI's developer portal for current timelines.

Writing an accurate description

The description tells a user or reviewer what the connector does, what data it accesses, and what it does not do. Be specific: "Reads events from your Google Calendar" is clearer than "provides calendar access." If the connector writes data, say so explicitly and give an example.

Keep the description current. A connector that gains new capabilities needs an updated description before those capabilities go live. A mismatch between the description and actual behavior is a common source of review rejections and user complaints.

A well-written description also explains why each permission is needed. Reviewers and users are more likely to trust a connector that explains its purpose clearly than one with a minimal description paired with a broad permissions request. If a scope looks surprising, address it in the description before the reviewer has to ask.

How to do this with fenbs

1. Create a free account and add a task for the connector release in your project.
2. Record authentication decisions in Decisions and rules: which method you chose, which scopes were approved, and who confirmed them.
3. Add each review requirement as a subtask with a status, so anyone picking up the release can see what is done and what remains.
4. Connect your AI via Integrations so it can read the release checklist at the start of each session and save its progress before stopping.
5. After publishing, record the distribution scope, release date, and approver as a decision so the team has a clear account of what went live.

For connector problems during testing, ChatGPT Connectors Not Working covers common failure points. For an overview of what connectors can access, see ChatGPT Connectors and Apps. Other connector-specific guides are in the connect-ai topic.