MCP Stdio- Hosted tools are not supported with the ChatCompletions API

[monuminu]

Hi Team

Trying to run the simple MCP code with Azure Chat Completion API and getting error.

Here is the code to replicate the issue.

import asyncio
import os
import shutil

from dotenv import load_dotenv
load_dotenv()

from agents import Agent, Runner, gen_trace_id, trace
from agents.mcp import MCPServer, MCPServerStdio
import os
from openai import AsyncAzureOpenAI
from agents import (
    OpenAIChatCompletionsModel,
    set_tracing_disabled,
    set_default_openai_client,
    set_default_openai_api,
    ModelSettings,
)
azure_client = AsyncAzureOpenAI(
    api_version=os.environ["AZURE_OPENAI_API_VERSION"],
    azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
    api_key=os.environ["AZURE_OPENAI_API_KEY"],
)

async def run(mcp_server: MCPServer):
    agent = Agent(
        name="Assistant",
        instructions="Use the tools to read the filesystem and answer questions based on those files.",
        mcp_servers=[mcp_server],
        model= OpenAIChatCompletionsModel(
                model="gpt-4o-mini",
                openai_client=azure_client,
            )
    )

    # List the files it can read
    message = "Read the files and list them."
    print(f"Running: {message}")
    result = await Runner.run(starting_agent=agent, input=message)
    print(result.final_output)

    # Ask about books
    message = "What is my #1 favorite book?"
    print(f"\n\nRunning: {message}")
    result = await Runner.run(starting_agent=agent, input=message)
    print(result.final_output)

    # Ask a question that reads then reasons.
    message = "Look at my favorite songs. Suggest one new song that I might like."
    print(f"\n\nRunning: {message}")
    result = await Runner.run(starting_agent=agent, input=message)
    print(result.final_output)


async def main():
    current_dir = os.path.dirname(os.path.abspath(__file__))
    samples_dir = os.path.join(current_dir, "sample_files")

    async with MCPServerStdio(
        name="Filesystem Server, via npx",
        params={
            "command": "npx",
            "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
        },
        client_session_timeout_seconds = 50
    ) as server:
        trace_id = gen_trace_id()
        with trace(workflow_name="MCP Filesystem Example", trace_id=trace_id):
            print(f"View trace: https://platform.openai.com/traces/trace?trace_id={trace_id}\n")
            await run(server)


if __name__ == "__main__":
    # Let's make sure the user has npx installed
    if not shutil.which("npx"):
        raise RuntimeError("npx is not installed. Please install it with `npm install -g npx`.")

    asyncio.run(main())

[monuminu]

Do not pass MCP as tools , instead pass it as mcp_server.