ChatGPT and Codex
Connect the DebugAI plugin to ChatGPT or Codex and sign in with your DebugAI account. Nothing to install.
The DebugAI plugin is a server DebugAI runs at https://mcp.debugai.io/mcp. ChatGPT and Codex connect to it over MCP and you sign in to DebugAI once, in your browser. It uses your normal DebugAI account, with the same plan and daily limit as the extension. If you have no account yet, that first sign-in creates a free one.
It has four tools: lookup_error, debug_error, report_outcome, and get_profile, which tells ChatGPT which account is connected.
It only sees what the conversation gives it
Unlike the extension and the npm MCP server, the plugin cannot read your files. It sees only what the model puts in the tool call. Paste the full error, with the stack trace, and the code around it. The more of the real code it gets, the more specific the answer.
ChatGPT
If DebugAI is listed when you search ChatGPT's plugins, install it from there and go to step 3. Otherwise add it yourself:
Add DebugAI as a custom MCP server
Open chatgpt.com/plugins, press the plus button and choose Add custom MCP server. Fill in:
| Field | Value |
|---|---|
| Name | DebugAI |
| MCP server URL | https://mcp.debugai.io/mcp |
| Authentication | OAuth |
Read the warning, choose I understand and want to continue, then Create as a plugin. ChatGPT lists the four tools it found.
Workspace policies can turn custom servers off. On a Business or Enterprise workspace, ask your admin.
Install it and sign in
Install the plugin. When ChatGPT sends you to DebugAI, sign in and approve. ChatGPT keeps a sign-in token for your DebugAI account until you disconnect the plugin.
Use it in a chat
Start a new conversation, type @ and pick DebugAI. Then paste the error and the code, and ask it to debug. When you have tried a fix, say so, for example "I tried fix 1 and it worked, record it". That calls report_outcome, and the next time the same error comes up, DebugAI leads with the fix that held.
You'll know it worked when
ChatGPT shows it used DebugAI, and the answer names a root cause and ranked fixes, each marked verified, failed check or not checked.
Codex
Codex keeps MCP servers in ~/.codex/config.toml. OpenAI's documentation says the Codex CLI, the IDE extension and the ChatGPT desktop app share that file, so this setup covers all three.
Add the server
codex mcp add debugai --url https://mcp.debugai.io/mcpThat writes this entry, which you can also add by hand:
[mcp_servers.debugai]
url = "https://mcp.debugai.io/mcp"Check it is there
Run codex mcp list, or type /mcp inside the codex session. DebugAI should be listed with its tools.
Projects and memory
Each tool call can name a project. A call that names none goes to a project called chatgpt, so ChatGPT and Codex share one memory unless you name your projects, for example "this is the checkout service". Memory here is separate from the memory the extension keeps for a folder on your machine.
What DebugAI receives
Only what each tool call carries: the error text and, when the model passes them, a code snippet, a file name, a language and a project name. Never your conversation. Before a file name is used, DebugAI removes your home folder from it and keeps the last three parts of the path. The details, including what is kept and for how long, are in the privacy policy.
To stop it, disconnect DebugAI in ChatGPT's or Codex's settings. Disconnecting does not delete what is already kept; email privacy@debugai.io from your account's address for that.
Checked on 28 October 2026
The ChatGPT and Codex steps follow OpenAI's own guides as of that date. Their menus change. If a label here no longer matches, the two things that matter are the address https://mcp.debugai.io/mcp and OAuth sign-in.
Next
- Work with your agent: when to call each tool.
- MCP tools: every input and output of the four tools.
- Want DebugAI to read your files? Use the npm server in a coding agent, or the extension.