m365-agents-py
Provides tooling for developing, hosting, and authenticating enterprise agents within the Microsoft 365 ecosystem.
Install
mkdir -p .claude/skills/m365-agents-py-comeonoliver && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16409" && unzip -o skill.zip -d .claude/skills/m365-agents-py-comeonoliver && rm skill.zipInstalls to .claude/skills/m365-agents-py-comeonoliver
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Host agent applications using aiohttp.
- →Route agent activities and messages.
- →Implement MSAL-based authentication for agents.
- →Manage conversation updates and messages.
- →Handle errors within the agent application.
- →Integrate with Copilot Studio.
How it works
The skill uses the Microsoft Agents SDK with aiohttp to create an AgentApplication that routes incoming activities and messages to specific handlers, managing state and authentication.
Inputs & outputs
When to use m365-agents-py
- →Building enterprise agents for Teams
- →Configuring Copilot Studio integration
- →Implementing MSAL-based auth
- →Setting up aiohttp agent hosting
About this skill
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.agentstomicrosoft_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>
Core Workflow: aiohttp-hosted AgentApplication
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))
AgentApplication Routing
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.")
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"),
)
copilot_client = CopilotCl
---
*Content truncated.*
When not to use it
- →When not building enterprise agents for Microsoft 365, Teams, or Copilot Studio.
- →When not using Python for agent development.
Prerequisites
Limitations
- →MemoryStorage is only for development use.
- →Import structure changed from `microsoft.agents` to `microsoft_agents`.
How it compares
This workflow provides a structured Python SDK for building Microsoft 365 agents with built-in routing and MSAL authentication, unlike manual HTTP server implementations.
Compared to similar skills
m365-agents-py side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| m365-agents-py (this skill) | 0 | 4mo | Review | Intermediate |
| mcp-builder | 136 | 3mo | Review | Advanced |
| copilot-sdk | 7 | 4mo | Review | Intermediate |
| openrouter-function-calling | 5 | 27d | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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