m365-agents-py
Microsoft 365 Agents SDK for Python. Build multichannel agents for Teams/M365/Copilot Studio with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based auth.
Install / Use
npx skills add microsoft/skills --skill m365-agents-pyInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of m365-agents-py
m365-agents-py scores 95/100 on our quality scale, 372nd of 3,481 Development & Engineering skills we index (top 11%).
Its SKILL.md is 14 KB long, well organised into 32 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.
With 3,051 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so m365-agents-py is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
m365-agents-py compared with similar skills
All 4 of these similar skills score higher than m365-agents-py; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| m365-agents-py (this skill)by microsoft | 95 | 3.1k | 5d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.1k | 13d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.1k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.4k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 2d ago | CLAUDE.md |
Frequently asked questions
- How do I install m365-agents-py?
- Run
npx skills add microsoft/skills --skill m365-agents-py. The install tabs above show the steps for each supported agent. - Which AI agents does m365-agents-py work with?
- It is written for GitHub Copilot, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is m365-agents-py safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is m365-agents-py still maintained?
- The repository was last updated 5 days ago, so m365-agents-py is actively maintained.
Skill content
View source on GitHubname: m365-agents-py description: | Microsoft 365 Agents SDK for Python. Build multichannel agents for Teams/M365/Copilot Studio with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based auth. Triggers: "Microsoft 365 Agents SDK", "microsoft_agents", "AgentApplication", "start_agent_process", "TurnContext", "Copilot Studio client", "CloudAdapter". license: MIT metadata: author: Microsoft version: "1.0.0" package: microsoft-agents-hosting-core, microsoft-agents-hosting-aiohttp, microsoft-agents-activity, microsoft-agents-authentication-msal, microsoft-agents-copilotstudio-client
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 (AAD auth via DefaultAzureCredential)
AZURE_OPENAI_ENDPOINT=<endpoint>
AZURE_OPENAI_API_VERSION=<version>
# Optional: Copilot Studio client
COPILOTSTUDIOAGENT__ENVIRONMENTID=<environment-id>
COPILOTSTUDIOAGENT__SCHEMANAME=<schema-name>
COPILOTSTUDIOAGENT__TENANTID=<tenant-id>
COPILOTSTUDIOAGENT__AGENTAPPID=<app-id>
Authentication & Lifecycle
🔑 Two rules apply to every code sample below:
- This SDK is async-first — use
async defhandlers andasync withthroughout.- Use explicit auth managers and context-managed network resources. Use
MsalConnectionManagerfor agent auth, and wrap per-request HTTP resources inasync with(for example,aiohttp.ClientSession).Snippets may abbreviate this setup, but production code should always follow both rules.
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 azure.identity import DefaultAzureCredential, get_bearer_token_provider
from microsoft_agents.activity import SensitivityUsageInfo
# AAD token provider (preferred over AZURE_OPENAI_API_KEY)
token_provider = get_…[redacted](
DefaultAzureCredential(),
"https://cognitiveservices.azure.com/.default",
)
# Module-level singleton: client lives for the agent app lifetime.
CLIENT = AsyncAzureOpenAI(
api_version=environ["AZURE_OPENAI_API_VERSION"],
azure_endpoint=environ["AZURE_OPENAI_ENDPOINT"],
azure_ad_token_provider=token_provider,
)
@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"),
)
# CopilotClient does not implement the context manager protocol.
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())
Best Practices
- **This SDK is async-first — use
async defhandlers and `asy
Truncated for display — read the full file on GitHub.
Related Skills
Agent-Reach
86.1kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
headroom
74.1kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
ai-job-search
44.4kThe job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.
claude-howto
41.7kA visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
