openai-agents using OpenAI Responses API with MCP traced with OpenTelemetry

main.py

# Add OpenAI and OpenTelemetry ENV variables to .env and run like this:
#   uv run -q --env-file .env main.py
#
# Note: Use a larger model like qwen3b:14b, if you are hosting your own models.
#
# /// script
# requires-python = ">=3.13"
# dependencies = [
#     "openai-agents",
#     "elastic-opentelemetry",
#     "elastic-opentelemetry-instrumentation-openai",
#     "opentelemetry-instrumentation-httpx"
# ]
# ///
import asyncio
import os

from agents import Agent, HostedMCPTool, ModelSettings, OpenAIProvider, Runner
from agents.tracing import GLOBAL_TRACE_PROVIDER
from opentelemetry.instrumentation import auto_instrumentation

# Shut down the global tracer as it sends to the OpenAI "/traces/ingest"
# endpoint, which we aren't using and doesn't exist on alternative backends
# like Ollama.
GLOBAL_TRACE_PROVIDER.shutdown()

auto_instrumentation.initialize()


async def main():
    model_name = os.getenv("CHAT_MODEL", "gpt-4o-mini")
    model = OpenAIProvider().get_model(model_name)
    agent = Agent(
        name="elasticsearch_agent",
        tools=[
            HostedMCPTool(
                tool_config={
                    "type": "mcp",
                    "server_label": "gitmcp",
                    "server_url": "https://gitmcp.io/elastic/elasticsearch",
                    "require_approval": "never",
                }
            )
        ],
        model=model,
        model_settings=ModelSettings(temperature=0),
    )

    res = await Runner.run(agent, "Which language is this repo written in?")
    print(res.final_output)


if __name__ == "__main__":
    asyncio.run(main())