Python: Show more authentication methods in Foundry Toolbox MCP (#5719)

* Show more authentication methods in Foundry Toolbox MCP * Remove hardcoded toolbox version num * Add Foundry MCP OAuth consent handling * Use message instead of the dedicated item type * Go back to using OAuthConsentRequestOutputItem * WIP: sample testing * Update error code * Address review on Foundry Toolbox MCP samples Reviewed feedback addressed: - Drop the branch-pinned `git+https://...@feature/...` entries from `04_foundry_toolbox/requirements.txt`; restore the simple comment + `mcp` runtime dep. The git pins were only useful while iterating on the PR and shouldn't ship. (eavanvalkenburg) - Fix the `/toolsets/` typo in both `04_foundry_toolbox/README.md` and `06_files/README.md`. Verified empirically against the research_toolbox in the test workspace: the toolbox MCP gateway lives at `/toolboxes/{name}/mcp?api-version=v1` and requires the `Foundry-Features: Toolboxes=V1Preview` header. `/toolsets/{name}/mcp` returns 403 with `preview_feature_required: Toolsets=V1Preview` (a different opt-in feature). - Wrap `httpx.AsyncClient(...)` in `async with ... as http_client:` in both samples so the connection pool is cleaned up. (Copilot reviewer) - Make the `TOOLBOX_NAME` env var consistent in both samples. Previously the tool name silently fell back to `"toolbox"` when `TOOLBOX_NAME` was unset, but `resolve_toolbox_endpoint()` still required `TOOLBOX_NAME` and would raise `KeyError`. The samples now resolve the endpoint once and derive the tool name from the resolved URL when `TOOLBOX_NAME` isn't set, so the local tool name always matches the upstream toolbox identity regardless of which env var the user set. (Copilot reviewer) - Rename `_responses.is_consent_error` to `consent_url_from_error`: the helper returns `str | None` (the consent URL), not a bool, so the new name matches behavior. Update the test class accordingly. (eavanvalkenburg) - Tighten `_handle_inner_agent`'s lazy-entry catch from `Exception` to `AgentFrameworkException`, the type the MCP layer actually wraps consent errors in via `MCPStreamableHTTPTool.__aenter__` → `ToolExecutionException(inner_exception=mcp_error)`. Network failures, cancellations, and other non-framework exceptions now propagate normally instead of being briefly caught and re-raised. The test helper `_make_consent_error` is updated to use `ToolExecutionException` so it matches the real-world wrapping. (eavanvalkenburg) - Clarify the `github_pat` description in `agent.manifest.yaml` to note it's only needed when the PAT-based connection (`github-mcp-pat-conn`) is chosen; users selecting the OAuth2 connection (`github-mcp-oauth-conn`) can leave it empty. (Copilot reviewer) Validation: ran both samples end-to-end against a real Foundry toolbox (`research_toolbox`) -- the samples connect successfully and the agent lists the toolbox's MCP tools (`api_specs___fetch_azure_rest_api_docs`, etc.). `uv run poe test -P foundry_hosting` passes (119 tests), pyright + mypy clean. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: fix broken Foundry samples link in 04_foundry_toolbox README The previous URL pointed to an old location of the toolbox supported-scenarios doc; the doc moved to /samples/python/hosted-agents/SUPPORTED_TOOLBOX_SCENARIOS.md and the old /samples/python/toolbox/azd path now 404s. Caught by the markdown-link-check CI step. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2026-05-20 05:00:38 -07:00
parent 72a6157c6a
commit d74d26c917
9 changed files with 537 additions and 127 deletions
@@ -1,5 +1,7 @@
 FROM python:3.12-slim

+RUN apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
+
 WORKDIR /app

 COPY . user_agent/
@@ -10,6 +10,20 @@ You can also create a Foundry Toolbox in the Foundry portal. Read more about it

 > If you set up a project with this sample and provision the resources using `azd provision`, a Foundry Toolbox will be created with the specified tools in [`agent.manifest.yaml`](agent.manifest.yaml).

+### Authentication Methods
+
+You can connect to MCP servers in Foundry Toolbox that use different authentication methods. This sample demonstrates the following authentication methods:
+
+- **No authentication**: The tool does not require any authentication. The agent can invoke the tool without providing any credentials. Sample MCP server: `https://gitmcp.io/Azure/azure-rest-api-specs`
+- **Key-based authentication**: The tool requires a key to authenticate. Sample MCP server: `https://api.githubcopilot.com/mcp` (GitHub MCP server) with a Personal Access Token (PAT) for authentication.
+- **OAuth2 authentication (managed)**: The tool requires OAuth2 to authenticate. Sample MCP server: `https://api.githubcopilot.com/mcp` (GitHub MCP server) with OAuth2 for authentication.
+- **Agent identity authentication**: The tool requires an agent identity token to authenticate. Sample MCP server: `https://{foundry-resource-name}.cognitiveservices.azure.com/language/mcp?api-version=2025-11-15-preview` (Azure Language MCP server) with agent identity for authentication.
+- **Entra Pass-through authentication**: The tool requires an Entra pass-through token to authenticate. Sample MCP server: Microsoft Outlook MCP server with Entra pass-through for authentication.
+
+> Definitions of these authentication methods can be found in the [agent.manifest.yaml](agent.manifest.yaml) file in this sample.
+
+There are also Non-MCP tools in the toolbox that support different authentication methods. Learn more at the [Foundry sample repository](https://github.com/microsoft-foundry/foundry-samples/blob/main/samples/python/hosted-agents/SUPPORTED_TOOLBOX_SCENARIOS.md).
+
 ## How It Works

 ### Model Integration
@@ -31,20 +45,20 @@ An extra environment variable must be set to point to the toolbox MCP endpoint.
 **Option A – Set `FOUNDRY_TOOLBOX_ENDPOINT` directly** (recommended for local development):

 ```bash
-export FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolsets/<name>/mcp?api-version=v1"
+export FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1"
 ```

 Or in PowerShell:

 ```powershell
-$env:FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolsets/<name>/mcp?api-version=v1"
+$env:FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1"
 ```

 **Option B – Set `TOOLBOX_NAME`** (used automatically by the Foundry hosting scaffolding after `azd provision`):

 The agent derives the endpoint at runtime as:
 ```
-{FOUNDRY_PROJECT_ENDPOINT}/toolsets/{TOOLBOX_NAME}/mcp?api-version=v1
+{FOUNDRY_PROJECT_ENDPOINT}/toolboxes/{TOOLBOX_NAME}/mcp?api-version=v1
 ```

 When deployed via `azd provision`, the scaffolding injects `TOOLBOX_NAME=agent-tools` and `FOUNDRY_PROJECT_ENDPOINT` automatically from the provisioned resources declared in [`agent.manifest.yaml`](agent.manifest.yaml).
@@ -18,16 +18,92 @@ template:
    - name: AZURE_AI_MODEL_DEPLOYMENT_NAME
      value: "{{AZURE_AI_MODEL_DEPLOYMENT_NAME}}"
    - name: TOOLBOX_NAME
-      value: "agent-tools"
+      value: "agent-tools-2"
+# parameters:
+#   properties:
+# - name: mcp_endpoint
+#   # `azd ai agent init -m` will prompt for this value when initializing the agent manifest
+#   secret: false
+#   description: URL of the public MCP server (e.g. https://gitmcp.io/Azure/azure-rest-api-specs) that does not require authentication
+# - name: github_pat
+#   # `azd ai agent init -m` will prompt for this value when initializing the agent manifest.
+#   # Only needed when the GitHub MCP connection is configured to use the `github-mcp-pat-conn`
+#   # PAT-based connection below; if you use the `github-mcp-oauth-conn` OAuth2 connection
+#   # instead, you can leave this empty.
+#   secret: true
+#   description: GitHub Personal Access Token used to authenticate with the GitHub MCP server (only needed when using the PAT connection; press Enter if using OAuth2 instead)
+# - name: language_mcp_entra_audience
+#   secret: false
+#   description: Entra ID audience for the Azure Language MCP server (e.g. https://cognitiveservices.azure.com/)
+# - name: language_mcp_target_url
+#   secret: false
+#   description: URL of the Azure Language MCP server that accepts agent identity tokens (e.g. https://{foundry-resource-name}.cognitiveservices.azure.com/language/mcp?api-version=2025-11-15-preview)
+# - name: outlook_mail_entra_audience
+#   secret: false
+#   description: Entra ID audience for the Outlook Mail MCP server
+# - name: outlook_mail_entra_mcp_target
+#   secret: false
+#   description: URL of the Outlook Mail MCP server that accepts user Entra tokens
 resources:
  - kind: model
    id: gpt-4.1-mini
    name: AZURE_AI_MODEL_DEPLOYMENT_NAME
-  - kind: toolbox
-    name: agent-tools
-    tools:
-      - type: web_search
-        name: web_search
-      - type: code_interpreter
-        name: code_interpreter
-
+  # - kind: connection
+  #   # A connection that uses a GitHub Personal Access Token (PAT) to authenticate with the GitHub MCP server
+  #   name: github-mcp-pat-conn
+  #   category: RemoteTool
+  #   authType: CustomKeys
+  #   target: https://api.githubcopilot.com/mcp
+  #   credentials:
+  #     type: CustomKeys
+  #     keys:
+  #       Authorization: "Bearer {{ github_pat }}"
+  # - kind: connection
+  #   # A connection that uses OAuth2 to authenticate with the GitHub MCP server
+  #   name: github-mcp-oauth-conn
+  #   category: RemoteTool
+  #   authType: OAuth2
+  #   target: https://api.githubcopilot.com/mcp
+  #   connectorName: foundrygithubmcp
+  #   credentials:
+  #     type: OAuth2
+  #     clientId: managed
+  #     clientSecret: managed
+  # - kind: connection
+  #   name: language-mcp-conn
+  #   category: RemoteTool
+  #   authType: AgenticIdentity
+  #   audience: "{{ language_mcp_entra_audience }}"
+  #   target: "{{ language_mcp_target_url }}"
+  # # - kind: connection
+  # #   name: outlook-mail-conn
+  # #   category: RemoteTool
+  # #   authType: UserEntraToken
+  # #   audience: "{{ outlook_mail_entra_audience }}"
+  # #   target: "{{ outlook_mail_entra_mcp_target }}"
+  # - kind: toolbox
+  #   name: agent-tools
+  #   tools:
+  #     - type: web_search
+  #       name: web_search
+  #     - type: code_interpreter
+  #       name: code_interpreter
+  #     # - type: mcp
+  #     #   # This MCP tool doesn't require authentication
+  #     #   server_label: noauth_mcp
+  #     #   server_url: "{{ mcp_endpoint }}"
+  #     #   require_approval: "never"
+  #     - type: mcp
+  #       # This MCP tool uses the GitHub MCP server with a PAT for authentication or OAuth2
+  #       server_label: github
+  #       project_connection_id: github-mcp-pat-conn # use `github-mcp-oauth-conn` for OAuth2 authentication
+  #       require_approval: "never"
+  #     - type: mcp
+  #       # This MCP tool uses the Azure Language MCP server with agent identity for authentication
+  #       server_label: language-mcp
+  #       project_connection_id: language-mcp-conn
+  #       require_approval: "never"
+  #     # - type: mcp
+  #     #   server_label: outlook-mail
+  #     #   project_connection_id: outlook-mail-conn
+  #     #   require_approval: "never"
@@ -3,12 +3,11 @@
 import asyncio
 import os
 from collections.abc import Callable
-from typing import Any

+import httpx
 from agent_framework import Agent, MCPStreamableHTTPTool
 from agent_framework.foundry import FoundryChatClient
 from agent_framework_foundry_hosting import ResponsesHostServer
-from azure.core.credentials import TokenCredential
 from azure.identity import DefaultAzureCredential, get_bearer_token_provider
 from dotenv import load_dotenv

@@ -16,7 +15,7 @@ from dotenv import load_dotenv
 load_dotenv()


-def _resolve_toolbox_endpoint() -> str:
+def resolve_toolbox_endpoint() -> str:
    """Resolve the toolbox MCP endpoint URL.

    Prefers the explicit ``FOUNDRY_TOOLBOX_ENDPOINT`` env var; falls back to
@@ -29,47 +28,61 @@ def _resolve_toolbox_endpoint() -> str:
        return endpoint
    project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"].rstrip("/")
    toolbox_name = os.environ["TOOLBOX_NAME"]
-    return f"{project_endpoint}/toolsets/{toolbox_name}/mcp?api-version=v1"
+    return f"{project_endpoint}/toolboxes/{toolbox_name}/mcp?api-version=v1"


-def make_toolbox_header_provider(credential: TokenCredential) -> Callable[[dict[str, Any]], dict[str, str]]:
-    """Build a header_provider that injects a fresh Azure AI bearer token on every MCP request."""
-    get_token = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
+class ToolboxAuth(httpx.Auth):
+    """Injects a fresh bearer token on every request."""

-    def provide(_kwargs: dict[str, Any]) -> dict[str, str]:
-        return {
-            "Authorization": f"Bearer {get_token()}",
-        }
+    def __init__(self, token_provider: Callable[[], str]):
+        self._get_token = token_provider

-    return provide
+    def auth_flow(self, request: httpx.Request):
+        request.headers["Authorization"] = f"Bearer {self._get_token()}"
+        yield request


 async def main():
    credential = DefaultAzureCredential()

-    client = FoundryChatClient(
-        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
-        model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
-        credential=credential,
-    )
+    # Create the toolbox
+    token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")

-    toolbox_tool = MCPStreamableHTTPTool(
-        name="foundry_toolbox",
-        description="Tools exposed by the configured Foundry toolbox",
-        url=_resolve_toolbox_endpoint(),
-        header_provider=make_toolbox_header_provider(credential),
-        load_prompts=False,
-    )
+    # Resolve the endpoint once and derive the tool name from the same source: when
+    # ``TOOLBOX_NAME`` isn't explicitly set, parse it out of the resolved URL so the
+    # tool's local name and the upstream toolbox always agree.
+    toolbox_endpoint = resolve_toolbox_endpoint()
+    toolbox_name = os.environ.get("TOOLBOX_NAME") or toolbox_endpoint.rsplit("/mcp", 1)[0].rsplit("/", 1)[-1]
+
+    async with httpx.AsyncClient(
+        auth=ToolboxAuth(token_provider),
+        headers={"Foundry-Features": "Toolboxes=V1Preview"},
+        timeout=120.0,
+    ) as http_client:
+        toolbox = MCPStreamableHTTPTool(
+            name=toolbox_name,
+            url=toolbox_endpoint,
+            http_client=http_client,
+            load_prompts=False,
+        )
+
+        # Create the chat client
+        client = FoundryChatClient(
+            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+            model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            credential=credential,
+        )
+
+        agent = Agent(
+            client=client,
+            instructions="You are a friendly assistant. Keep your answers brief.",
+            tools=toolbox,
+            # History will be managed by the hosting infrastructure, thus there
+            # is no need to store history by the service. Learn more at:
+            # https://developers.openai.com/api/reference/resources/responses/methods/create
+            default_options={"store": False},
+        )

-    async with Agent(
-        client=client,
-        instructions="You are a friendly assistant. Keep your answers brief.",
-        tools=toolbox_tool,
-        # History will be managed by the hosting infrastructure, thus there
-        # is no need to store history by the service. Learn more at:
-        # https://developers.openai.com/api/reference/resources/responses/methods/create
-        default_options={"store": False},
-    ) as agent:
        server = ResponsesHostServer(agent)
        await server.run_async()

@@ -1,2 +1,4 @@
-agent-framework
-agent-framework-foundry-hosting
+# agent-framework
+# agent-framework-foundry-hosting
+
+mcp>=1.24.0,<2
@@ -21,9 +21,10 @@ This agent uses four tools:
 1. **Get Current Working Directory Tool (`get_cwd`)** – Returns the current working directory of the agent host process.
 2. **List Files Tool (`list_files`)** – Lists the files in a specified directory.
 3. **Read File Tool (`read_file`)** – Reads the contents of a specified file.
-4. **Code Interpreter Tool (`code_interpreter`)** – Allows the agent to execute Python code in a safe.
+4. **Code Interpreter Tool (`code_interpreter`)** – Allows the agent to execute Python code in a safe sandboxed environment.
+5. **Web Search Tool (`web_search`)** – Allows the agent to perform web searches using the Bing Search API.

-> In this sample, the filesystem tools are function tools defined in Python using the `@tool` decorator from the Agent Framework. The code interpreter tool is a managed tool provided by [Foundry Toolbox](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/toolbox). Learn more about foundry toolbox integration with hosted agents with this [sample](../04_foundry_toolbox/).
+> In this sample, the filesystem tools are function tools defined in Python using the `@tool` decorator from the Agent Framework. The code interpreter tool and web search tool are managed tools provided by [Foundry Toolbox](https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/toolbox). Learn more about foundry toolbox integration with hosted agents with this [sample](../04_foundry_toolbox/).

 ## Running the Agent Host

@@ -34,20 +35,20 @@ An extra environment variable must be set to point to the toolbox MCP endpoint.
 **Option A – Set `FOUNDRY_TOOLBOX_ENDPOINT` directly** (recommended for local development):

 ```bash
-export FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolsets/<name>/mcp?api-version=v1"
+export FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1"
 ```

 Or in PowerShell:

 ```powershell
-$env:FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolsets/<name>/mcp?api-version=v1"
+$env:FOUNDRY_TOOLBOX_ENDPOINT="https://<account>.services.ai.azure.com/api/projects/<project>/toolboxes/<name>/mcp?api-version=v1"
 ```

 **Option B – Set `TOOLBOX_NAME`** (used automatically by the Foundry hosting scaffolding after `azd provision`):

 The agent derives the endpoint at runtime as:
 ```
-{FOUNDRY_PROJECT_ENDPOINT}/toolsets/{TOOLBOX_NAME}/mcp?api-version=v1
+{FOUNDRY_PROJECT_ENDPOINT}/toolboxes/{TOOLBOX_NAME}/mcp?api-version=v1
 ```

 When deployed via `azd provision`, the scaffolding injects `TOOLBOX_NAME=agent-tools` and `FOUNDRY_PROJECT_ENDPOINT` automatically from the provisioned resources declared in [`agent.manifest.yaml`](agent.manifest.yaml).
@@ -3,12 +3,11 @@
 import asyncio
 import os
 from collections.abc import Callable
-from typing import Any

+import httpx
 from agent_framework import Agent, MCPStreamableHTTPTool, tool
 from agent_framework.foundry import FoundryChatClient
 from agent_framework_foundry_hosting import ResponsesHostServer
-from azure.core.credentials import TokenCredential
 from azure.identity import DefaultAzureCredential, get_bearer_token_provider
 from dotenv import load_dotenv

@@ -16,7 +15,7 @@ from dotenv import load_dotenv
 load_dotenv()


-def _resolve_toolbox_endpoint() -> str:
+def resolve_toolbox_endpoint() -> str:
    """Resolve the toolbox MCP endpoint URL.

    Prefers the explicit ``FOUNDRY_TOOLBOX_ENDPOINT`` env var; falls back to
@@ -29,19 +28,18 @@ def _resolve_toolbox_endpoint() -> str:
        return endpoint
    project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"].rstrip("/")
    toolbox_name = os.environ["TOOLBOX_NAME"]
-    return f"{project_endpoint}/toolsets/{toolbox_name}/mcp?api-version=v1"
+    return f"{project_endpoint}/toolboxes/{toolbox_name}/mcp?api-version=v1"


-def make_toolbox_header_provider(credential: TokenCredential) -> Callable[[dict[str, Any]], dict[str, str]]:
-    """Build a header_provider that injects a fresh Azure AI bearer token on every MCP request."""
-    get_token = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
+class ToolboxAuth(httpx.Auth):
+    """Injects a fresh bearer token on every request."""

-    def provide(_kwargs: dict[str, Any]) -> dict[str, str]:
-        return {
-            "Authorization": f"Bearer {get_token()}",
-        }
+    def __init__(self, token_provider: Callable[[], str]):
+        self._get_token = token_provider

-    return provide
+    def auth_flow(self, request: httpx.Request):
+        request.headers["Authorization"] = f"Bearer {self._get_token()}"
+        yield request


@tool(description="Get the current working directory.", approval_mode="never_require")
@@ -75,39 +73,47 @@ def read_file(file_path: str) -> str:
 async def main():
    credential = DefaultAzureCredential()

-    client = FoundryChatClient(
-        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
-        model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
-        credential=credential,
-    )
+    # Create the toolbox
+    token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")

-    # Connect to the toolbox MCP endpoint and expose only the code_interpreter tool.
-    # The toolbox deployed has two tools: (see agent.manifest.yaml)
-    # - `code_interpreter`
-    # - `web_search`
-    # We only need the `code_interpreter` tool for this sample.
-    toolbox_tool = MCPStreamableHTTPTool(
-        name="foundry_toolbox",
-        description="Tools exposed by the configured Foundry toolbox",
-        url=_resolve_toolbox_endpoint(),
-        header_provider=make_toolbox_header_provider(credential),
-        load_prompts=False,
-        allowed_tools=["code_interpreter"],
-    )
+    # Resolve the endpoint once and derive the tool name from the same source: when
+    # ``TOOLBOX_NAME`` isn't explicitly set, parse it out of the resolved URL so the
+    # tool's local name and the upstream toolbox always agree.
+    toolbox_endpoint = resolve_toolbox_endpoint()
+    toolbox_name = os.environ.get("TOOLBOX_NAME") or toolbox_endpoint.rsplit("/mcp", 1)[0].rsplit("/", 1)[-1]

-    async with Agent(
-        client=client,
-        instructions=(
-            "You are a friendly assistant. Keep your answers brief. "
-            "Make sure all mathematical calculations are performed using the code interpreter "
-            "instead of mental arithmetic."
-        ),
-        tools=[get_cwd, list_files, read_file, toolbox_tool],
-        # History will be managed by the hosting infrastructure, thus there
-        # is no need to store history by the service. Learn more at:
-        # https://developers.openai.com/api/reference/resources/responses/methods/create
-        default_options={"store": False},
-    ) as agent:
+    async with httpx.AsyncClient(
+        auth=ToolboxAuth(token_provider),
+        headers={"Foundry-Features": "Toolboxes=V1Preview"},
+        timeout=120.0,
+    ) as http_client:
+        toolbox = MCPStreamableHTTPTool(
+            name=toolbox_name,
+            url=toolbox_endpoint,
+            http_client=http_client,
+            load_prompts=False,
+        )
+
+        # Create the chat client
+        client = FoundryChatClient(
+            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+            model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+            credential=credential,
+        )
+
+        agent = Agent(
+            client=client,
+            instructions=(
+                "You are a friendly assistant. Keep your answers brief. "
+                "Make sure all mathematical calculations are performed using the code interpreter "
+                "instead of mental arithmetic."
+            ),
+            tools=[get_cwd, list_files, read_file, toolbox],
+            # History will be managed by the hosting infrastructure, thus there
+            # is no need to store history by the service. Learn more at:
+            # https://developers.openai.com/api/reference/resources/responses/methods/create
+            default_options={"store": False},
+        )
        server = ResponsesHostServer(agent)
        await server.run_async()