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Add this skill
npx mdskills install sickn33/m365-agents-pyComprehensive SDK integration guide with routing, streaming, and auth examples but over-scoped permissions
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.
⚠️ Breaking Change: Recent updates have changed the Python import structure from
microsoft.agentstomicrosoft_agents(using underscores instead of dots).
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
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=
# Optional: OAuth handlers for auto sign-in
AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__GRAPH__SETTINGS__AZUREBOTOAUTHCONNECTIONNAME=
# Optional: Azure OpenAI for streaming
AZURE_OPENAI_ENDPOINT=
AZURE_OPENAI_API_VERSION=
AZURE_OPENAI_API_KEY=
# Optional: Copilot Studio client
COPILOTSTUDIOAGENT__ENVIRONMENTID=
COPILOTSTUDIOAGENT__SCHEMANAME=
COPILOTSTUDIOAGENT__TENANTID=
COPILOTSTUDIOAGENT__AGENTAPPID=
import logging
from os import environ
from dotenv import load_dotenv
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
AGENT_APP = AgentApplication[TurnState](
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))
import re
from microsoft_agents.hosting.core import (
AgentApplication, TurnState, TurnContext, MessageFactory
)
from microsoft_agents.activity import ActivityTypes
AGENT_APP = AgentApplication[TurnState](
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.")
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()
@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']}!")
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"),
)
copilot_client = CopilotClient(settings, token)
# Start conversation
act = copilot_client.start_conversation(True)
async for action in act:
if action.text:
print(action.text)
# Ask question
replies = copilot_client.ask_question("Hello!", action.conversation.id)
async for reply in replies:
if reply.type == ActivityTypes.message:
print(reply.text)
asyncio.run(main())
microsoft_agents import prefix (underscores, not dots).MemoryStorage only for development; use BlobStorage or CosmosDB in production.load_configuration_from_env(environ) to load SDK configuration.jwt_authorization_middleware in aiohttp Application middlewares.MsalConnectionManager for MSAL-based authentication.end_stream() in finally blocks when using streaming responses.auth_handlers parameter on message decorators for OAuth-protected routes.| File | Contents |
|---|---|
| references/acceptance-criteria.md | Import paths, hosting pipeline, streaming, OAuth, and Copilot Studio patterns |
| 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 |
Install via CLI
npx mdskills install sickn33/m365-agents-pyM365 Agents Py is a free, open-source AI agent skill. |
Install M365 Agents Py with a single command:
npx mdskills install sickn33/m365-agents-pyThis downloads the skill files into your project and your AI agent picks them up automatically.
M365 Agents Py works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code, Factory. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.