Python: Show more authentication methods in Foundry Toolbox MCP

python/samples/04-hosting/foundry-hosted-agents/responses/04_foundry_toolbox/README.md

@@ -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/tree/main/samples/python/toolbox/azd#supported-scenarios).
+
 ## How It Works
 
 ### Model Integration

python/samples/04-hosting/foundry-hosted-agents/responses/04_foundry_toolbox/agent.manifest.yaml

@@ -19,15 +19,88 @@ template:
       value: "{{AZURE_AI_MODEL_DEPLOYMENT_NAME}}"
     - name: TOOLBOX_NAME
       value: "agent-tools"
+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
+      secret: true
+      description: GitHub Personal Access Token used to authenticate with the GitHub MCP server (press Enter if OAuth2 is used 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: 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"

python/samples/04-hosting/foundry-hosted-agents/responses/04_foundry_toolbox/main.py

@@ -3,20 +3,19 @@
 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
 
 # Load environment variables from .env file
 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
@@ -29,42 +28,50 @@ 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()
 
+    # Create the toolbox
+    token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
+
+    http_client = httpx.AsyncClient(
+        auth=ToolboxAuth(token_provider),
+        headers={"Foundry-Features": "Toolboxes=V1Preview"},
+        timeout=120.0,
+    )
+
+    toolbox = MCPStreamableHTTPTool(
+        name=os.environ.get("TOOLBOX_NAME", "toolbox"),
+        url=resolve_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,
     )
 
-    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,
-    )
-
     async with Agent(
         client=client,
         instructions="You are a friendly assistant. Keep your answers brief.",
-        tools=toolbox_tool,
+        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

python/samples/04-hosting/foundry-hosted-agents/responses/06_files/README.md

@@ -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
 

python/samples/04-hosting/foundry-hosted-agents/responses/06_files/main.py

@@ -3,20 +3,19 @@
 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
 
 # Load environment variables from .env file
 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")
@@ -75,34 +73,37 @@ def read_file(file_path: str) -> str:
 async def main():
     credential = DefaultAzureCredential()
 
+    # Create the toolbox
+    token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
+
+    http_client = httpx.AsyncClient(
+        auth=ToolboxAuth(token_provider),
+        headers={"Foundry-Features": "Toolboxes=V1Preview"},
+        timeout=120.0,
+    )
+
+    toolbox = MCPStreamableHTTPTool(
+        name=os.environ.get("TOOLBOX_NAME", "toolbox"),
+        url=resolve_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,
     )
 
-    # 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"],
-    )
-
     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],
+        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