ChatGPT, OpenAI API & Codex

Use the Data MCP server from ChatGPT, from your own app through the OpenAI Responses API or Agents SDK, and from the Codex CLI.

#ChatGPT

ChatGPT connects to remote MCP servers through developer mode and apps. Developer mode is available to Business, Enterprise and Edu workspaces on the web and must be enabled by a workspace admin; check OpenAI's help center for the current menu path.

ChatGPT cannot send an API key. It supports OAuth or no authentication only, so the connection is always made with OAuth and is always live.

1. In ChatGPT, create a custom connector or app for the MCP server URL https://data-services.autouncle.com/mcp and choose OAuth.
2. ChatGPT registers itself through dynamic client registration (AutoUncle does not publish a client ID metadata document).
3. Sign in with your AutoUncle account, choose the organization and approve the scopes.

Each successful valuation uses one of the organization's credits. Approve catalogue:read and account:read without valuations:write if you only want ChatGPT to look up vehicles.

#Responses API

The Responses API can call a remote MCP server for you. Send the key in headers, keep it in your backend, and decide when tools may run without approval:

import os

from openai import OpenAI

client = OpenAI()
response = client.responses.create(
    model="your-model",
    input="Value a 2020 Volkswagen Golf in Denmark with 60,000 km. Report the price basis, currency, 80% interval and precision grade.",
    tools=[
        {
            "type": "mcp",
            "server_label": "autouncle-data",
            "server_url": "https://data-services.autouncle.com/mcp",
            "headers": {"Authorization": f"Bearer {os.environ['AUTOUNCLE_API_KEY']}"},
            "allowed_tools": ["get_account", "search_vehicles", "valuate_car", "get_valuation"],
            "require_approval": {"never": {"tool_names": ["get_account", "search_vehicles", "get_valuation"]}},
        }
    ],
)
print(response.output_text)

• headers is sent to the MCP server on every call. Use a test key while you build.
• require_approval defaults to requiring approval for every tool call. The example lets the free, read-only tools run directly and keeps approval for valuate_car, which spends a credit with a live key.
• allowed_tools limits which tools the model sees.
• If your app runs the OAuth flow itself, pass the access token as authorization instead of an Authorization header.

Replace your-model with the model you use.

#Agents SDK

In the OpenAI Agents SDK for Python, connect to the server over Streamable HTTP from your own process:

import os

from agents.mcp import MCPServerStreamableHttp

autouncle = MCPServerStreamableHttp(
    params={
        "url": "https://data-services.autouncle.com/mcp",
        "headers": {"Authorization": f"Bearer {os.environ['AUTOUNCLE_API_KEY']}"},
    }
)

Pass the server to your agent's mcp_servers and use it inside async with autouncle: as the SDK documentation shows. The SDK also offers HostedMCPTool, which runs the call through the Responses API with the same tool_config fields as the JSON above.

#Codex CLI

Codex reads MCP servers from ~/.codex/config.toml (or .codex/config.toml in a trusted project). With an API key, name the environment variable that holds it; Codex sends it as a bearer token:

[mcp_servers.autouncle-data]
url = "https://data-services.autouncle.com/mcp"
bearer_token_env_var = "AUTOUNCLE_API_KEY"

For OAuth, add the server without a token and sign in:

codex mcp add autouncle-data --url https://data-services.autouncle.com/mcp
codex mcp login autouncle-data

#Verify the connection

Ask the model or agent:

Call get_account on autouncle-data and tell me the key mode, scopes and remaining credits.

#Troubleshooting

#Next steps

• Safety & spend control
• Tool reference

Sources: OpenAI MCP and connectors guide, Responses API reference, Building an MCP server for ChatGPT, ChatGPT app authentication, ChatGPT developer mode, Agents SDK MCP, Codex MCP.