Python Bug in azure-ai-agentserver-responses: MCP Tool OBO Token Exchange Fails When Agent is Deployed to Azure AI Foundry

[mitokic]

Summary

When using FoundryChatClient.get_mcp_tool() to attach a Foundry MCP server that requires OAuth (Work IQ User / mcp_MeServer) to an agent, the tool works correctly locally via agent-framework directly, but fails with an OBO token error when the same agent is deployed as a hosted agent on Azure AI Foundry Agent Service.

Environment

Package	Version
azure-ai-agentserver-responses	1.0.0b5
agent-framework	1.2.2
agent-framework-openai	1.2.2
agent-framework-foundry	1.2.2
agent-framework-foundry-hosting	≥1.0.0a260429
azure-ai-projects	≥2.1.0
azure-identity	≥1.26.0b1
Python	3.12
Container base	python:3.12-slim
Foundry protocol	Responses API v1.0.0

Error

When the deployed agent invokes the MCP tool, the following exception is raised:

agent_framework.exceptions.ChatClientException: (
  '<class \'agent_framework_foundry._chat_client.FoundryChatClient\'> service failed to complete the prompt:
   Failed to fetch access token. Status: BadRequest.
   Details: "ARA OBO token request failed with status BadRequest"',
  APIError('Failed to fetch access token. Status: BadRequest.
   Details: "ARA OBO token request failed with status BadRequest"')
)

Reproduction

Agent setup (simplified)

# agent.py
from azure.identity.aio import DefaultAzureCredential
from agent_framework import Agent
from agent_framework.foundry import FoundryChatClient

def create_orchestrator_agent() -> Agent:
    credential = DefaultAzureCredential()

    client = FoundryChatClient(
        project_endpoint="https://<foundry-project-endpoint>",
        model="<model-deployment-name>",
        credential=credential,
    )

    mcp_tool = FoundryChatClient.get_mcp_tool(
        name="WorkIQUser",
        url="https://agent365.svc.cloud.microsoft/agents/servers/mcp_MeServer",
        project_connection_id="<mcp-connection-id>",
        approval_mode="never_require",
    )

    return Agent(
        client=client,
        name="MyAgent",
        instructions="You are a helpful assistant. Use the MCP tool to get the user's profile.",
        tools=[mcp_tool],
    )

Container entrypoint (simplified)

# container.py
import asyncio
from agent_framework_foundry_hosting import ResponsesHostServer
from agent import create_orchestrator_agent

async def main():
    orchestrator = create_orchestrator_agent()
    server = ResponsesHostServer(orchestrator)
    await server.run_async()

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

Hosted agent deployment

from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
    HostedAgentDefinition,
    ProtocolVersionRecord,
    AgentProtocol,
)

client = AIProjectClient(
    endpoint="<foundry-project-endpoint>",
    credential=credential,
    allow_preview=True,
)

agent = client.agents.create_version(
    agent_name="my-agent",
    definition=HostedAgentDefinition(
        container_protocol_versions=[
            ProtocolVersionRecord(protocol=AgentProtocol.RESPONSES, version="1.0.0"),
        ],
        image="<acr>.azurecr.io/my-agent:<tag>",
        environment_variables={...},
        tools=[
            {
                "type": "mcp",
                "server_label": "WorkIQUser",
                "server_url": "https://agent365.svc.cloud.microsoft/agents/servers/mcp_MeServer",
                "project_connection_id": "<mcp-connection-id>",
            }
        ],
    ),
)

Invocation (triggers the error)

openai_client = client.get_openai_client(agent_name="my-agent")

# This call triggers the MCP tool, which fails with OBO error
response = openai_client.responses.create(
    input=[{"type": "message", "role": "user", "content": "What is my email?"}],
)

Works locally

Running the same agent directly via agent-framework locally works without error:

# interactive.py or notebook
orchestrator = create_orchestrator_agent()
session = orchestrator.create_session()

# MCP tool call succeeds — DefaultAzureCredential resolves to user's Azure CLI token
result = await orchestrator.run("What is my email?", session=session)
print(result.text)  # ✓ Returns user profile from Graph API

Expected behavior

The MCP tool should successfully acquire an OBO token and call the MCP server (mcp_MeServer) to retrieve the user's Graph API profile, the same way it works when running agent-framework locally.

Questions

1. What OAuth/app registration configuration is required for hosted agent MCP tools to perform OBO token exchange successfully?
2. Is there a known limitation with OBO token exchange for MCP tools in hosted agents?

[mitokic]

Linking this issue from older versions of agentserver packages: #45797

[JimItCapacity]

The problem is not only in Python, somewhere in the last 24 hours this bug has been introduced, and when we use the .NET Azure.AI.Projects 1.2.0-beta.5 package it goes wrong as well:

After the first failed request of a conversation, we can ask follow up questions, but the agent is large incapable of answering questions that it could answer just fine before yesterday:

We see this across multiple Foundry portals.

[mvsmal]

We are having the same problem using .NET Azure.AI.Projects 2.1.0-beta.1. Yesterday it worked fine. Was there any Foundry change from Microsoft?

[mitokic]

I have never been able to use it correctly with the Work IQ user MCP tool in Foundry. Works locally, but not when deployed. Been trying to get it to work for months.

[graemefoster]

I was trying to recreate OBO as done by work-iq, for my own Foundry Agent (using MCP tool). WorkIq is fine through Foundry Agent, but my own MCP server - "ARA OBO token request failed with status BadRequest"

[mitokic]

I was able to get the WorkIQ Foundry team to work in a deployed hosted agent. I first had to delete the existing Foundry tool for WorkIQ, create it from scratch again and save. Then I added it into a toolbox inside of Foundry that my agent framework agent now calls instead. And that worked! If the results hold I will be closing out this issue in a few days.