OpenAI: Responses API, Agents SDK, Codex and ChatGPT

import os
from openai import OpenAI

client = OpenAI()

response = client.responses.create(
    model="gpt-6-astra",  # the model named in OpenAI's MCP guide on 2026-09-17; any model that supports the mcp tool works
    tools=[{
        "type": "mcp",
        "server_label": "routeur",
        "server_description": "Prediction markets on Kalshi and Polymarket: proven relations, prices, leads, history. Read-only.",
        "server_url": "https://api.routeur.app/mcp",
        "headers": {"Authorization": f"Bearer {os.environ['ROUTEUR_API_KEY']}"},
        "require_approval": "never",
        "allowed_tools": [
            "search_markets", "compare_venues", "explain_relation",
            "market_snapshot", "find_opportunities",
        ],
    }],
    input="Compare the Detroit vs Buffalo total points market across venues. Name the venue with every price and say how old the prices are.",
)

print(response.output_text)

import asyncio
import os

from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

INSTRUCTIONS = """You read prediction markets through Routeur. Prices are asks per contract that pays $1, as decimal strings; the spread is yes_ask + no_ask - 1 and is a cost, not an edge.
A relation is proven from contract terms, never guessed; no relation means "not proven", not "unrelated".
A gap between venues is money only if depth.executable is true. Strategy and calibration figures are settled history before fees, not forecasts.
Name the venue and observed_at with every price. Use at most four Routeur tool calls per answer. Never give investment advice; nothing here places orders."""

async def main() -> None:
    async with MCPServerStreamableHttp(
        name="routeur",
        params={
            "url": "https://api.routeur.app/mcp",
            "headers": {"Authorization": f"Bearer {os.environ['ROUTEUR_API_KEY']}"},
            "timeout": 30,
        },
        cache_tools_list=True,
        max_retry_attempts=3,
    ) as routeur:
        agent = Agent(name="Market analyst", instructions=INSTRUCTIONS, mcp_servers=[routeur])
        result = await Runner.run(agent, "Brief me on the Detroit vs Buffalo total points market.")
        print(result.final_output)

asyncio.run(main())