m365-agents-py

Supporting material availability

This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files:

• <support-root>/references/acceptance-criteria.md

Ask for the original supporting material or an existing installation before using a step that depends on these paths; this catalog does not identify a verified download source for them. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable.

Microsoft 365 Agents SDK (Python)

Build enterprise agents for Microsoft 365, Teams, and Copilot Studio using the Microsoft Agents SDK with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based authentication.

Before implementation

• Use the microsoft-docs MCP to verify the latest API signatures for AgentApplication, start_agent_process, and authentication options.
• Confirm package versions on PyPI for the microsoft-agents-* packages you plan to use.

Important Notice - Import Changes

⚠️ Breaking Change: Recent updates have changed the Python import structure from microsoft.agents to microsoft_agents (using underscores instead of dots).

Installation

pip install microsoft-agents-hosting-core
pip install microsoft-agents-hosting-aiohttp
pip install microsoft-agents-activity
pip install microsoft-agents-authentication-msal
pip install microsoft-agents-copilotstudio-client
pip install python-dotenv aiohttp

Environment Variables (.env)

CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=<client-id>
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=<client-secret>
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=<tenant-id>

# Optional: OAuth handlers for auto sign-in
AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__GRAPH__SETTINGS__AZUREBOTOAUTHCONNECTIONNAME=<connection-name>

# Optional: Azure OpenAI for streaming
AZURE_OPENAI_ENDPOINT=<endpoint>
AZURE_OPENAI_API_VERSION=<version>
AZURE_OPENAI_API_KEY=<key>

# Optional: Copilot Studio client
COPILOTSTUDIOAGENT__ENVIRONMENTID=<environment-id>
COPILOTSTUDIOAGENT__SCHEMANAME=<schema-name>
COPILOTSTUDIOAGENT__TENANTID=<tenant-id>
COPILOTSTUDIOAGENT__AGENTAPPID=<app-id>

Snippets require a version-pinned SDK and the setup/imports shown across sections; duplicate /me handlers are alternatives, not meant to be registered together. Use synthetic messages and authorized identities; preserve middleware verification and do not expose secrets, private turns or tokens through logs/cloud tracing. Configure the Azure OpenAI model field with your actual deployment name, not an assumed public model ID.

Core Workflow: aiohttp-hosted AgentApplication

import logging
from os import environ

from dotenv import load_dotenv
import aiohttp
from aiohttp.web import Request, Response, Application, run_app

from microsoft_agents.activity import load_configuration_from_env
from microsoft_agents.hosting.core import (
    Authorization,
    AgentApplication,
    TurnState,
    TurnContext,
    MemoryStorage,
)
from microsoft_agents.hosting.aiohttp import (
    CloudAdapter,
    start_agent_process,
    jwt_authorization_middleware,
)
from microsoft_agents.authentication.msal import MsalConnectionManager

# Enable logging
ms_agents_logger = logging.getLogger("microsoft_agents")
ms_agents_logger.addHandler(logging.StreamHandler())
ms_agents_logger.setLevel(logging.INFO)

# Load configuration
load_dotenv()
agents_sdk_config = load_configuration_from_env(environ)

# Create storage and connection manager
STORAGE = MemoryStorage()
CONNECTION_MANAGER = MsalConnectionManager(**agents_sdk_config)
ADAPTER = CloudAdapter(connection_manager=CONNECTION_MANAGER)
AUTHORIZATION = Authorization(STORAGE, CONNECTION_MANAGER, **agents_sdk_config)

# Create AgentApplication
ApplicationType = AgentApplication[TurnState]
AGENT_APP = ApplicationType(
    storage=STORAGE, adapter=ADAPTER, authorization=AUTHORIZATION, **agents_sdk_config
)


@AGENT_APP.conversation_update("membersAdded")
async def on_members_added(context: TurnContext, _state: TurnState):
    await context.send_activity("Welcome to the agent!")


@AGENT_APP.activity("message")
async def on_message(context: TurnContext, _state: TurnState):
    await context.send_activity(f"You said: {context.activity.text}")


@AGENT_APP.error
async def on_error(context: TurnContext, error: Exception):
    await context.send_activity("The agent encountered an error.")


# Server setup
async def entry_point(req: Request) -> Response:
    agent: AgentApplication = req.app["agent_app"]
    adapter: CloudAdapter = req.app["adapter"]
    return await start_agent_process(req, agent, adapter)


APP = Application(middlewares=[jwt_authorization_middleware])
APP.router.add_post("/api/messages", entry_point)
APP["agent_configuration"] = CONNECTION_MANAGER.get_default_connection_configuration()
APP["agent_app"] = AGENT_APP
APP["adapter"] = AGENT_APP.adapter

if __name__ == "__main__":
    run_app(APP, host="localhost", port=environ.get("PORT", 3978))

AgentApplication Routing

import re
from microsoft_agents.hosting.core import (
    AgentApplication, TurnState, TurnContext, MessageFactory
)
from microsoft_agents.activity import Activity, ActivityTypes

ApplicationType = AgentApplication[TurnState]
AGENT_APP = ApplicationType(
    storage=STORAGE, adapter=ADAPTER, authorization=AUTHORIZATION, **agents_sdk_config
)

# Welcome handler
@AGENT_APP.conversation_update("membersAdded")
async def on_members_added(context: TurnContext, _state: TurnState):
    await context.send_activity("Welcome!")

# Regex-based message handler
@AGENT_APP.message(re.compile(r"^hello$", re.IGNORECASE))
async def on_hello(context: TurnContext, _state: TurnState):
    await context.send_activity("Hello!")

# Simple string message handler
@AGENT_APP.message("/status")
async def on_status(context: TurnContext, _state: TurnState):
    await context.send_activity("Status: OK")

# Auth-protected message handler
@AGENT_APP.message("/me", auth_handlers=["GRAPH"])
async def on_profile(context: TurnContext, state: TurnState):
    token_response = await AGENT_APP.auth.get_token(context, "GRAPH")
    if token_response and token_response.token:
        # Use token to call Graph API
        await context.send_activity("Profile retrieved")

# Invoke activity handler
@AGENT_APP.activity(ActivityTypes.invoke)
async def on_invoke(context: TurnContext, _state: TurnState):
    invoke_response = Activity(
        type=ActivityTypes.invoke_response, value={"status": 200}
    )
    await context.send_activity(invoke_response)

# Fallback message handler
@AGENT_APP.activity("message")
async def on_message(context: TurnContext, _state: TurnState):
    await context.send_activity(f"Echo: {context.activity.text}")

# Error handler
@AGENT_APP.error
async def on_error(context: TurnContext, error: Exception):
    await context.send_activity("An error occurred.")

Streaming Responses with Azure OpenAI

from openai import AsyncAzureOpenAI
from microsoft_agents.activity import SensitivityUsageInfo

CLIENT = AsyncAzureOpenAI(
    api_version=environ["AZURE_OPENAI_API_VERSION"],
    azure_endpoint=environ["AZURE_OPENAI_ENDPOINT"],
    api_key=environ["AZURE_OPENAI_API_KEY"]
)

@AGENT_APP.message("poem")
async def on_poem_message(context: TurnContext, _state: TurnState):
    # Configure streaming response
    context.streaming_response.set_feedback_loop(True)
    context.streaming_response.set_generated_by_ai_label(True)
    context.streaming_response.set_sensitivity_label(
        SensitivityUsageInfo(
            type="https://schema.org/Message",
            schema_type="CreativeWork",
            name="Internal",
        )
    )
    context.streaming_response.queue_informative_update("Starting a poem...\n")

    # Stream from Azure OpenAI
    streamed_response = await CLIENT.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": "You are a creative assistant."},
            {"role": "user", "content": "Write a poem about Python."}
        ],
        stream=True,
    )
    
    try:
        async for chunk in streamed_response:
            if chunk.choices and chunk.choices[0].delta.content:
                context.streaming_response.queue_text_chunk(
                    chunk.choices[0].delta.content
                )
    finally:
        await context.streaming_response.end_stream()

OAuth / Auto Sign-In

@AGENT_APP.message("/logout")
async def logout(context: TurnContext, state: TurnState):
    await AGENT_APP.auth.sign_out(context, "GRAPH")
    await context.send_activity(MessageFactory.text("You have been logged out."))


@AGENT_APP.message("/me", auth_handlers=["GRAPH"])
async def profile_request(context: TurnContext, state: TurnState):
    user_token_response = await AGENT_APP.auth.get_token(context, "GRAPH")
    if user_token_response and user_token_response.token:
        # Use token to call Microsoft Graph
        async with aiohttp.ClientSession() as session:
            headers = {
                "Authorization": f"Bearer {user_token_response.token}",
                "Content-Type": "application/json",
            }
            async with session.get(
                "https://graph.microsoft.com/v1.0/me", headers=headers
            ) as response:
                if response.status == 200:
                    user_info = await response.json()
                    await context.send_activity(f"Hello, {user_info['displayName']}!")

Copilot Studio Client (Direct to Engine)

import asyncio
from msal import PublicClientApplication
from microsoft_agents.activity import ActivityTypes, load_configuration_from_env
from microsoft_agents.copilotstudio.client import (
    ConnectionSettings,
    CopilotClient,
)

# Token cache (local file for interactive flows)
class LocalTokenCache:
    # See samples for full implementation
    pass

def acquire_token(settings, app_client_id, tenant_id):
    pca = PublicClientApplication(
        client_id=app_client_id,
        authority=f"https://login.microsoftonline.com/{tenant_id}",
    )
    
    token_request = {"scopes": ["https://api.powerplatform.com/.default"]}
    accounts = pca.get_accounts()
    
    if accounts:
        response = pca.acquire_token_silent(token_request["scopes"], account=accounts[0])
        return response.get("access_token")
    else:
        response = pca.acquire_token_interactive(**token_request)
        return response.get("access_token")


async def main():
    settings = ConnectionSettings(
        environment_id=environ.get("COPILOTSTUDIOAGENT__ENVIRONMENTID"),
        agent_identifier=environ.get("COPILOTSTUDIOAGENT__SCHEMANAME"),
    )
    
    token = acquire_token(
        settings,
        app_client_id=environ.get("COPILOTSTUDIOAGENT__AGENTAPPID"),
        tenant_id=environ.get("COPILOTSTUDIOAGENT__TENANTID"),
    )
    
    if not token:
        raise RuntimeError("Token acquisition failed")
    copilot_client = CopilotClient(settings, token)
    
    # Start conversation
    conversation_id = None
    act = copilot_client.start_conversation(True)
    async for action in act:
        if action.conversation:
            conversation_id = action.conversation.id
        if action.text:
            print(action.text)
    
    # Ask question
    if not conversation_id:
        raise RuntimeError("No conversation ID returned")
    replies = copilot_client.ask_question("Hello!", conversation_id)
    async for reply in replies:
        if reply.type == ActivityTypes.message:
            print(reply.text)


asyncio.run(main())

Best Practices

1. Use microsoft_agents import prefix (underscores, not dots).
2. Use MemoryStorage only for development; use BlobStorage or CosmosDB in production.
3. Always use load_configuration_from_env(environ) to load SDK configuration.
4. Include jwt_authorization_middleware in aiohttp Application middlewares.
5. Use MsalConnectionManager for MSAL-based authentication.
6. Call end_stream() in finally blocks when using streaming responses.
7. Use auth_handlers parameter on message decorators for OAuth-protected routes.
8. Keep secrets in environment variables, not in source code.

Reference Files

File	Contents
references/acceptance-criteria.md	Import paths, hosting pipeline, streaming, OAuth, and Copilot Studio patterns

Reference Links

Resource	URL
Microsoft 365 Agents SDK	https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/
GitHub samples (Python)	https://github.com/microsoft/Agents-for-python
PyPI packages	https://pypi.org/search/?q=microsoft-agents
Integrate with Copilot Studio	https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/integrate-with-mcs

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.