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To connect an MCP server, configure it in an assistant that supports the connection method it needs, complete any required authentication, inspect the tools it exposes, and limit access to the people and actions that need it. Then verify permissions on the server itself: an assistant’s settings do not replace the server’s authorization checks.
The exact setup depends on the host and where the server runs. The steps below cover custom MCP apps in ChatGPT and MCP servers in Visual Studio Code (VS Code). ChatGPT’s documented custom-app setup applies to Business and Enterprise/Edu on the web; feature availability and interface details can vary by workspace and rollout.
What connecting an MCP server means
An MCP server makes tools or other context available to an AI assistant through the host’s MCP integration. Depending on the assistant and server, you may connect to a remote endpoint or start a local server process. The host then uses the connection to discover what the server offers and, when allowed, make those tools available to the assistant.
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There are two permission layers to manage. The assistant host controls who can use the connection and which advertised actions the assistant may call. The server must also authenticate and authorize requests according to its own implementation. Restricting an action in the host is useful, but it is not a substitute for server-side access control.
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Before configuring anything, establish how the server is meant to be reached, which authentication it expects, and which tools or data it exposes. A remote URL, local command, and private-network connection are different deployment choices, not interchangeable entries in a setup form.
Choose a connection method that fits the server
Use the host’s documented configuration format and transport support. The main decision is where the process or endpoint lives and how the assistant can reach it.
| Server location or method | What the host connects to | Important consideration |
|---|---|---|
| Remote server | An endpoint URL, using a transport supported by the assistant | Confirm the endpoint is reachable from the host and that its authentication flow is supported. |
| Local server | A command and its arguments, started by the host | A local MCP server can execute code on the machine. Review its publisher and configuration before starting it. |
| Private-network server with an OpenAI Secure MCP Tunnel | An outbound connection from a client running inside the private network, relaying MCP requests | The server does not need a public listener. Tunnel roles remain separate from ChatGPT workspace permissions. |
The tunnel option is documented for supported OpenAI products; do not assume another assistant offers the same method. If a server is private-network-only, check the specific host’s supported networking approach rather than exposing it publicly by default.
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OpenAI’s Help Center documents custom MCP apps in ChatGPT Business and Enterprise/Edu on the web. The documented flow requires an administrator to enable developer mode. An authorized user can then create and configure an app, while an administrator or owner publishes it after testing and review.
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- Confirm workspace eligibility and policy. Ask a workspace administrator whether developer mode and custom MCP apps are available. OpenAI describes full MCP support, including write and modify actions, as rolling out in beta, so availability and the current interface can differ between workspaces.
- Have an administrator enable developer mode. This is a workspace-level prerequisite in the documented setup, not a permission granted merely by knowing the server URL.
- Create a custom app and enter its connection details. Supply the server endpoint and the requested app metadata. Use the endpoint and connection information provided by the server’s operator; do not substitute an unverified address.
- Select and complete authentication. Follow the configured provider’s flow and grant only the access needed for the app. For OAuth, check the refresh-token behavior before relying on a connection to persist.
- Scan the advertised tools and review the actions. Inspect what the server exposes before making the app available. Select only the actions and groups required for the intended users.
- Create a draft, test it, then publish through the workspace process. The documented process has an administrator or owner publish after testing and review. Treat the draft as a review point, not as evidence that every exposed action should be enabled.
Control ChatGPT access after setup
ChatGPT administrators can govern which groups have access and which actions are allowed. Keep access groups narrow enough to match the work the app is meant to support. A user who can access an app should not automatically receive every action its server advertises.
When the server’s tool list is refreshed, newly discovered actions are disabled by default. Changes to existing action definitions are surfaced for review. Examine these changes deliberately before enabling anything: an added or altered action can affect what the assistant is able to request from the server.
OpenAI warns that connecting to an unsafe or untrusted MCP server can increase exposure to security risks, including prompt injection. A successful connection only shows that the host can communicate with the server; it does not establish that the server is trustworthy or that its tools are safe for your data.
Add an MCP server in Visual Studio Code
VS Code supports user-level and workspace MCP configurations. Its current documentation recommends portable destinations such as a workspace .mcp.json file or the user-level ~/.copilot/mcp-config.json for new configurations. VS Code also documents .vscode/mcp.json and user-profile configuration for compatibility. Use the location appropriate to whether the server should be available in one workspace or to the user more broadly.
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- Choose the configuration scope. Use a workspace configuration when the server belongs with a particular project, or a user-level configuration when it should be available across the user’s workspaces. Consider who can read or change a workspace configuration before adding sensitive connection details.
- Add the server in the documented format. For a remote server, provide its HTTP URL. For a local server, provide the command and arguments needed to start it. Follow the current VS Code MCP documentation for the exact configuration syntax and any authentication settings; do not assume configuration formats are identical across assistants.
- Check trust before starting a local server. Review the publisher and configuration. VS Code cautions that local MCP servers can run arbitrary code on the machine.
- Use the MCP: List Servers command. Run this command to inspect and manage configured servers. Review the listed server and its available tools before using them.
- Resolve any workspace-trust prompt intentionally. Workspace trust affects whether workspace servers can start, and VS Code has separate trust decisions for other sources. Do not bypass a trust decision without understanding which configuration or server it applies to.
OAuth in VS Code
VS Code’s developer guide describes an OAuth workflow tied to the MCP authorization specification. It notes identity-provider requirements, including dynamic client registration or client credentials in the described flow. These are implementation details of VS Code’s documented workflow, not universal MCP requirements. Check that guide and the identity provider’s configuration before selecting OAuth; a provider may need setup beyond a server URL and a login prompt.
Configure OAuth so access does not unexpectedly expire
Authentication establishes who or what is connecting; authorization determines what that identity may do. For an OAuth-protected server, verify the provider, requested scopes, and token behavior as part of setup. A successful first login does not guarantee that access will renew automatically.
OpenAI specifically recommends checking the provider’s discovery metadata to confirm that refresh tokens are issued. Look for offline_access or an equivalent capability, and confirm that the provider supports it. Without refresh-token renewal, a connection can expire and require the user to authenticate again. The exact provider behavior and supported flow depend on the implementation.
Do not treat VS Code-specific redirect URLs or identity-provider setup as rules every MCP host must follow. Follow the selected host’s current OAuth instructions and the server operator’s requirements, then test the connection in the same way users will rely on it.
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Set permissions on both the host and the server
Permission management should limit both who can reach the integration and what requests it can make. The assistant may provide user, group, or action controls; the server must enforce its own authorization for protected resources and operations.
- Limit users or groups. In ChatGPT, choose only the groups that need the app. Review membership when the app’s purpose or audience changes.
- Limit enabled actions. Enable only the tools required for the task. In ChatGPT, review newly discovered actions and changed definitions after a refresh rather than treating a refreshed list as automatically approved.
- Keep server-side authorization in force. Configure the server to authenticate requests and authorize access as appropriate for its design. Host-side action selection should not be the only barrier protecting data or operations.
- Grant OAuth scopes deliberately. Check what the requested scopes permit and whether token renewal works. Avoid granting broader access simply to get past a setup prompt.
- Protect secrets from assistant-generated code and logs. OpenAI’s Agents API guidance says to keep secrets out of reusable agent definitions and logs. When credentials must remain inaccessible to agent-generated code, use a trusted proxy or server to hold them.
- Recheck after changes. Revisit tool definitions, enabled actions, access groups, authentication, and workspace policies after a server update or policy change.
For a local VS Code server, trust review is also part of permission management: the server may execute code on the user’s machine. For a remote server, verify its identity and endpoint before sending it credentials or allowing it to handle requests.
Test the integration before making it routine
Testing should establish both that the connection works and that the permission boundary behaves as intended. A server can be reachable while exposing more actions or access than users need.
- Confirm the server identity. Check the publisher, endpoint or local configuration, and expected purpose against information from the server’s operator.
- Inspect the advertised tools. Compare the discovered actions with the task the integration is meant to support. Investigate unexpected tools or changed definitions before enabling them.
- Test the authentication lifecycle. Complete sign-in, verify the expected access, and confirm how renewal or reauthentication works. For OAuth, check refresh-token support rather than assuming the initial login persists.
- Verify the access boundary. Confirm that only intended users or groups can use the integration and only intended actions are enabled. Check that the server continues to enforce its own authorization.
- Retest after updates. When server tools, authentication, workspace policies, or configuration change, repeat the relevant checks. In ChatGPT, newly discovered actions being disabled by default helps prevent automatic enablement, but the changed tool list still needs review.
Common setup problems and what to check
The assistant cannot reach the server
First determine whether the server is local, remotely reachable, or private-network-only. Check that the host supports the configured connection method and that the endpoint or local command matches the server operator’s instructions. A private server that has no public listener will not become reachable merely by entering its address in a host form; for supported OpenAI products, the documented Secure MCP Tunnel uses an outbound client inside the network.
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The OAuth login works, but access later stops
Check whether the provider issues refresh tokens and supports offline_access or an equivalent. If it does not, users may need to authenticate again after the current access expires. Also verify the scopes and identity-provider requirements for the particular host rather than assuming one host’s OAuth settings apply to another.
A configured VS Code server does not start
Check the selected configuration file and its command or HTTP URL, then use MCP: List Servers to inspect the configured server. If it is workspace-provided, consider whether workspace trust is preventing it from starting. Review the publisher and code before approving a local server, since local MCP servers can execute arbitrary code.
A ChatGPT app or action is unavailable
Check whether the workspace is eligible for the documented custom-app flow, whether an administrator enabled developer mode, and whether the app has been published through the workspace’s review process. Custom MCP support and write or modify actions are subject to rollout and beta availability. If an action appeared after a refresh, inspect it and enable it only if the workspace policy and intended use permit it.
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Reduce access at both layers: narrow the ChatGPT groups or enabled actions where those controls are available, and adjust server-side authorization. Reinspect the advertised tools after server changes. Do not rely on a successful sign-in as proof that every available action is appropriate for every user.
Keep the setup current
Host documentation, labels, and supported flows can change, especially while features are rolling out. OpenAI’s Help Center and Microsoft’s VS Code MCP documentation describe product-specific setup; the MCP authorization specification is versioned and should not be mistaken for every host’s exact implementation. Before a production rollout, check the selected host’s current documentation and workspace settings, then review the connection and permissions whenever the server or its policies change.
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