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Show more authentication methods in Foundry Toolbox MCP
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Tao Chen
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eavanvalkenburg
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eavanvalkenburg
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@@ -10,6 +10,20 @@ You can also create a Foundry Toolbox in the Foundry portal. Read more about it
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> 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).
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### Authentication Methods
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You can connect to MCP servers in Foundry Toolbox that use different authentication methods. This sample demonstrates the following authentication methods:
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- **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`
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- **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.
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- **OAuth2 authentication (managed)**: The tool requires OAuth2 to authenticate. Sample MCP server: `https://api.githubcopilot.com/mcp` (GitHub MCP server) with OAuth2 for authentication.
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- **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.
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- **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.
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> Definitions of these authentication methods can be found in the [agent.manifest.yaml](agent.manifest.yaml) file in this sample.
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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).
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## How It Works
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### Model Integration
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+74
-1
@@ -19,10 +19,65 @@ template:
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value: "{{AZURE_AI_MODEL_DEPLOYMENT_NAME}}"
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- name: TOOLBOX_NAME
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value: "agent-tools"
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parameters:
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properties:
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- name: mcp_endpoint
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# `azd ai agent init -m` will prompt for this value when initializing the agent manifest
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secret: false
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description: URL of the public MCP server (e.g. https://gitmcp.io/Azure/azure-rest-api-specs) that does not require authentication
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- name: github_pat
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# `azd ai agent init -m` will prompt for this value when initializing the agent manifest
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secret: true
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description: GitHub Personal Access Token used to authenticate with the GitHub MCP server (press Enter if OAuth2 is used instead)
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- name: language_mcp_entra_audience
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secret: false
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description: Entra ID audience for the Azure Language MCP server (e.g. https://cognitiveservices.azure.com/)
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- name: language_mcp_target_url
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secret: false
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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)
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- name: outlook_mail_entra_audience
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secret: false
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description: Entra ID audience for the Outlook Mail MCP server
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- name: outlook_mail_entra_mcp_target
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secret: false
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description: URL of the Outlook Mail MCP server that accepts user Entra tokens
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resources:
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- kind: model
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id: gpt-4.1-mini
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name: AZURE_AI_MODEL_DEPLOYMENT_NAME
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- kind: connection
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# A connection that uses a GitHub Personal Access Token (PAT) to authenticate with the GitHub MCP server
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name: github-mcp-pat-conn
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category: RemoteTool
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authType: CustomKeys
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target: https://api.githubcopilot.com/mcp
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credentials:
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type: CustomKeys
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keys:
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Authorization: "Bearer {{ github_pat }}"
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- kind: connection
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# A connection that uses OAuth2 to authenticate with the GitHub MCP server
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name: github-mcp-oauth-conn
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category: RemoteTool
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authType: OAuth2
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target: https://api.githubcopilot.com/mcp
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connectorName: foundrygithubmcp
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credentials:
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type: OAuth2
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clientId: managed
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clientSecret: managed
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- kind: connection
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name: language-mcp-conn
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category: RemoteTool
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authType: AgenticIdentity
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audience: "{{ language_mcp_entra_audience }}"
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target: "{{ language_mcp_target_url }}"
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- kind: connection
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name: outlook-mail-conn
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category: RemoteTool
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authType: UserEntraToken
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audience: "{{ outlook_mail_entra_audience }}"
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target: "{{ outlook_mail_entra_mcp_target }}"
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- kind: toolbox
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name: agent-tools
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tools:
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@@ -30,4 +85,22 @@ resources:
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name: web_search
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- type: code_interpreter
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name: code_interpreter
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- type: mcp
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# This MCP tool doesn't require authentication
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server_label: noauth_mcp
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server_url: "{{ mcp_endpoint }}"
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require_approval: "never"
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- type: mcp
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# This MCP tool uses the GitHub MCP server with a PAT for authentication or OAuth2
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server_label: github
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project_connection_id: github-mcp-pat-conn # use `github-mcp-oauth-conn` for OAuth2 authentication
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require_approval: "never"
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- type: mcp
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# This MCP tool uses the Azure Language MCP server with agent identity for authentication
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server_label: language-mcp
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project_connection_id: language-mcp-conn
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require_approval: "never"
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- type: mcp
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server_label: outlook-mail
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project_connection_id: outlook-mail-conn
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require_approval: "never"
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+28
-21
@@ -3,12 +3,11 @@
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import asyncio
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import os
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from collections.abc import Callable
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from typing import Any
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import httpx
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from agent_framework import Agent, MCPStreamableHTTPTool
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from agent_framework.foundry import FoundryChatClient
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from agent_framework_foundry_hosting import ResponsesHostServer
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from azure.core.credentials import TokenCredential
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from azure.identity import DefaultAzureCredential, get_bearer_token_provider
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from dotenv import load_dotenv
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@@ -16,7 +15,7 @@ from dotenv import load_dotenv
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load_dotenv()
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def _resolve_toolbox_endpoint() -> str:
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def resolve_toolbox_endpoint() -> str:
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"""Resolve the toolbox MCP endpoint URL.
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Prefers the explicit ``FOUNDRY_TOOLBOX_ENDPOINT`` env var; falls back to
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@@ -29,42 +28,50 @@ def _resolve_toolbox_endpoint() -> str:
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return endpoint
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project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"].rstrip("/")
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toolbox_name = os.environ["TOOLBOX_NAME"]
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return f"{project_endpoint}/toolsets/{toolbox_name}/mcp?api-version=v1"
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return f"{project_endpoint}/toolboxes/{toolbox_name}/versions/29/mcp?api-version=v1"
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def make_toolbox_header_provider(credential: TokenCredential) -> Callable[[dict[str, Any]], dict[str, str]]:
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"""Build a header_provider that injects a fresh Azure AI bearer token on every MCP request."""
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get_token = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
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class ToolboxAuth(httpx.Auth):
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"""Injects a fresh bearer token on every request."""
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def provide(_kwargs: dict[str, Any]) -> dict[str, str]:
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return {
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"Authorization": f"Bearer {get_token()}",
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}
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def __init__(self, token_provider: Callable[[], str]):
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self._get_token = token_provider
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return provide
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def auth_flow(self, request: httpx.Request):
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request.headers["Authorization"] = f"Bearer {self._get_token()}"
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yield request
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async def main():
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credential = DefaultAzureCredential()
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# Create the toolbox
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token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
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http_client = httpx.AsyncClient(
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auth=ToolboxAuth(token_provider),
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headers={"Foundry-Features": "Toolboxes=V1Preview"},
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timeout=120.0,
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)
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toolbox = MCPStreamableHTTPTool(
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name=os.environ.get("TOOLBOX_NAME", "toolbox"),
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url=resolve_toolbox_endpoint(),
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http_client=http_client,
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load_prompts=False,
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)
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# Create the chat client
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client = FoundryChatClient(
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project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
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model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
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credential=credential,
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)
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toolbox_tool = MCPStreamableHTTPTool(
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name="foundry_toolbox",
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description="Tools exposed by the configured Foundry toolbox",
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url=_resolve_toolbox_endpoint(),
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header_provider=make_toolbox_header_provider(credential),
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load_prompts=False,
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)
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async with Agent(
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client=client,
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instructions="You are a friendly assistant. Keep your answers brief.",
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tools=toolbox_tool,
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tools=toolbox,
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# History will be managed by the hosting infrastructure, thus there
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# is no need to store history by the service. Learn more at:
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# https://developers.openai.com/api/reference/resources/responses/methods/create
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@@ -21,9 +21,10 @@ This agent uses four tools:
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1. **Get Current Working Directory Tool (`get_cwd`)** – Returns the current working directory of the agent host process.
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2. **List Files Tool (`list_files`)** – Lists the files in a specified directory.
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3. **Read File Tool (`read_file`)** – Reads the contents of a specified file.
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4. **Code Interpreter Tool (`code_interpreter`)** – Allows the agent to execute Python code in a safe.
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4. **Code Interpreter Tool (`code_interpreter`)** – Allows the agent to execute Python code in a safe sandboxed environment.
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5. **Web Search Tool (`web_search`)** – Allows the agent to perform web searches using the Bing Search API.
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> 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/).
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> 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/).
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## Running the Agent Host
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@@ -3,12 +3,11 @@
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import asyncio
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import os
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from collections.abc import Callable
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from typing import Any
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import httpx
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from agent_framework import Agent, MCPStreamableHTTPTool, tool
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from agent_framework.foundry import FoundryChatClient
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from agent_framework_foundry_hosting import ResponsesHostServer
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from azure.core.credentials import TokenCredential
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from azure.identity import DefaultAzureCredential, get_bearer_token_provider
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from dotenv import load_dotenv
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@@ -16,7 +15,7 @@ from dotenv import load_dotenv
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load_dotenv()
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def _resolve_toolbox_endpoint() -> str:
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def resolve_toolbox_endpoint() -> str:
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"""Resolve the toolbox MCP endpoint URL.
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Prefers the explicit ``FOUNDRY_TOOLBOX_ENDPOINT`` env var; falls back to
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@@ -29,19 +28,18 @@ def _resolve_toolbox_endpoint() -> str:
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return endpoint
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project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"].rstrip("/")
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toolbox_name = os.environ["TOOLBOX_NAME"]
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return f"{project_endpoint}/toolsets/{toolbox_name}/mcp?api-version=v1"
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return f"{project_endpoint}/toolboxes/{toolbox_name}/mcp?api-version=v1"
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def make_toolbox_header_provider(credential: TokenCredential) -> Callable[[dict[str, Any]], dict[str, str]]:
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"""Build a header_provider that injects a fresh Azure AI bearer token on every MCP request."""
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get_token = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
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class ToolboxAuth(httpx.Auth):
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"""Injects a fresh bearer token on every request."""
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def provide(_kwargs: dict[str, Any]) -> dict[str, str]:
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return {
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"Authorization": f"Bearer {get_token()}",
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}
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def __init__(self, token_provider: Callable[[], str]):
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self._get_token = token_provider
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return provide
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def auth_flow(self, request: httpx.Request):
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request.headers["Authorization"] = f"Bearer {self._get_token()}"
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yield request
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@tool(description="Get the current working directory.", approval_mode="never_require")
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@@ -75,26 +73,29 @@ def read_file(file_path: str) -> str:
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async def main():
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credential = DefaultAzureCredential()
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# Create the toolbox
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token_provider = get_bearer_token_provider(credential, "https://ai.azure.com/.default")
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http_client = httpx.AsyncClient(
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auth=ToolboxAuth(token_provider),
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headers={"Foundry-Features": "Toolboxes=V1Preview"},
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timeout=120.0,
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)
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toolbox = MCPStreamableHTTPTool(
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name=os.environ.get("TOOLBOX_NAME", "toolbox"),
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url=resolve_toolbox_endpoint(),
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http_client=http_client,
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load_prompts=False,
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)
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# Create the chat client
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client = FoundryChatClient(
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project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
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model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
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credential=credential,
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)
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# Connect to the toolbox MCP endpoint and expose only the code_interpreter tool.
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# The toolbox deployed has two tools: (see agent.manifest.yaml)
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# - `code_interpreter`
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# - `web_search`
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# We only need the `code_interpreter` tool for this sample.
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toolbox_tool = MCPStreamableHTTPTool(
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name="foundry_toolbox",
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description="Tools exposed by the configured Foundry toolbox",
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url=_resolve_toolbox_endpoint(),
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header_provider=make_toolbox_header_provider(credential),
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load_prompts=False,
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allowed_tools=["code_interpreter"],
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)
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async with Agent(
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client=client,
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instructions=(
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@@ -102,7 +103,7 @@ async def main():
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"Make sure all mathematical calculations are performed using the code interpreter "
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"instead of mental arithmetic."
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),
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tools=[get_cwd, list_files, read_file, toolbox_tool],
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tools=[get_cwd, list_files, read_file, toolbox],
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# History will be managed by the hosting infrastructure, thus there
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# is no need to store history by the service. Learn more at:
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# https://developers.openai.com/api/reference/resources/responses/methods/create
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