OpenAI API and Agents SDK

1. 1

   Responses API: declare the server as a tool with the key as authorization.

   PythonCopy

   from openai import OpenAI
   import os
   
   client = OpenAI()
   response = client.responses.create(
       model="gpt-5",
       input="Who are the top commenters on r/python this week?",
       tools=[{
           "type": "mcp",
           "server_label": "zomler",
           "server_url": "https://api.zomler.com/mcp",
           "authorization": os.environ["ZOMLER_API_KEY"],
           "require_approval": "never",
       }],
   )

2. 2

   Agents SDK: the same server as a HostedMCPTool on the agent.

   Agents SDKCopy

   from agents import Agent, HostedMCPTool
   
   agent = Agent(
       name="analyst",
       tools=[HostedMCPTool(tool_config={
           "type": "mcp",
           "server_label": "zomler",
           "server_url": "https://api.zomler.com/mcp",
           "authorization": os.environ["ZOMLER_API_KEY"],
           "require_approval": "never",
       })],
   )

One tool per platform, plus capabilities and check_balance, at https://api.zomler.com/mcp. Every answer is the envelope: what was measured, when, what was left out and why, and what it cost. Fresh fetches spend credits; anything already held is free.

Keys are created under API keys in the dashboard, where each one's calls and spend are listed. Revoking a key stops this client on its next call. The same key also calls the REST API.

All clients