How to integrate Microsoft teams MCP with CrewAI

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Introduction

This guide walks you through connecting Microsoft teams to CrewAI using the Composio tool router. By the end, you'll have a working Microsoft teams agent that can add new member to project team, schedule an online meeting for sales, list all chats i’m part of, get details for marketing team channel through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Microsoft teams account through Composio's Microsoft teams MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Microsoft teams connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Microsoft teams
  • Build a conversational loop where your agent can execute Microsoft teams operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Microsoft teams MCP server, and what's possible with it?

The Microsoft Teams MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Microsoft Teams account. It provides structured and secure access to your Teams workspace, so your agent can perform actions like managing chats, sending messages, creating meetings, and organizing teams on your behalf.

  • Automated chat and message management: Let your agent retrieve, read, and summarize messages from any Teams chat, or fetch all chats you’re part of for quick updates.
  • Team and channel organization: Easily create new teams, add members, get channel details, or archive and delete teams to keep your workspace organized.
  • Scheduling online meetings: Have your agent schedule standalone Teams meetings instantly, making it simple to coordinate with colleagues or clients without manual setup.
  • Granular access to team and chat details: Fetch full information about specific teams, channels, or even individual messages with precision, enabling rich contextual workflows.
  • Seamless membership and collaboration management: Add or update members in teams with a prompt, ensuring the right people always have access to the conversations and resources they need.

Supported Tools & Triggers

Tools
Add member to teamTool to add a user to a microsoft teams team.
Archive Teams teamTool to archive a microsoft teams team.
Get all chatsRetrieves all microsoft teams chats a specified user is part of, supporting filtering, property selection, and pagination.
Get all chat messagesRetrieves all messages from a specified microsoft teams chat using the microsoft graph api, automatically handling pagination; ensure `chat id` is valid and odata expressions in `filter` or `select` are correct.
Create online meetingUse to schedule a new standalone microsoft teams online meeting, i.
Create TeamTool to create a new microsoft teams team.
Delete Teams teamTool to delete a microsoft teams team.
Get team channelTool to get a specific channel in a team.
Get chat messageTool to get a specific chat message.
Get TeamTool to get a specific team.
List message repliesTool to list replies to a channel message.
List team membersTool to list members of a microsoft teams team.
List Teams templatesTool to list available microsoft teams templates.
List usersTool to list all users in the organization.
Create a channelCreates a new 'standard', 'private', or 'shared' channel within a specified microsoft teams team.
Create ChatCreates a new chat; if a 'oneonone' chat with the specified members already exists, its details are returned, while 'group' chats are always newly created.
Get Teams messageRetrieves a specific message from a microsoft teams channel using its team, channel, and message ids.
List TeamsRetrieves microsoft teams accessible by the authenticated user, allowing filtering, property selection, and pagination.
List team channelsRetrieves channels for a specified microsoft teams team id (must be valid and for an existing team), with options to include shared channels, filter results, and select properties.
List chat messagesRetrieves messages (newest first) from an existing and accessible microsoft teams one-on-one chat, group chat, or channel thread, specified by `chat id`.
List PeopleRetrieves a list of people relevant to a specified user from microsoft graph, noting the `search` parameter is only effective if `user id` is 'me'.
Post message to Teams channelPosts a new text or html message to a specified channel in a microsoft teams team.
Send message to Teams chatSends a non-empty message (text or html) to a specified, existing microsoft teams chat; content must be valid html if `content type` is 'html'.
Reply to Teams channel messageSends a reply to an existing message, identified by `message id`, within a specific `channel id` of a given `team id` in microsoft teams.
Unarchive Teams teamTool to unarchive a microsoft teams team.
Update Teams channel messageTool to update a message in a channel.
Update Teams chat messageTool to update a specific message in a chat.
Update TeamTool to update the properties of a team.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Microsoft teams connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Microsoft teams via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Microsoft teams MCP URL

Create a Composio Tool Router session for Microsoft teams

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["microsoft_teams"],
)
url = session.mcp.url
What's happening:
  • You create a Microsoft teams only session through Composio
  • Composio returns an MCP HTTP URL that exposes Microsoft teams tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Microsoft teams Assistant",
    goal="Help users interact with Microsoft teams through natural language commands",
    backstory=(
        "You are an expert assistant with access to Microsoft teams tools. "
        "You can perform various Microsoft teams operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Microsoft teams MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Microsoft teams operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Microsoft teams related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_microsoft_teams_agent.py

Complete Code

Here's the complete code to get you started with Microsoft teams and CrewAI:

python
# file: crewai_microsoft_teams_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Microsoft teams session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["microsoft_teams"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Microsoft teams assistant agent
    toolkit_agent = Agent(
        role="Microsoft teams Assistant",
        goal="Help users interact with Microsoft teams through natural language commands",
        backstory=(
            "You are an expert assistant with access to Microsoft teams tools. "
            "You can perform various Microsoft teams operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Microsoft teams operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Microsoft teams related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Microsoft teams through Composio's Tool Router. The agent can perform Microsoft teams operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Microsoft teams MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Microsoft teams MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Microsoft teams MCP with Claude Agent SDK

Google ADK

Google ADK

Use Microsoft teams MCP with Google ADK

LangChain

LangChain

Use Microsoft teams MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Microsoft teams MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Microsoft teams MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Microsoft teams MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Microsoft teams MCP?

With a standalone Microsoft teams MCP server, the agents and LLMs can only access a fixed set of Microsoft teams tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Microsoft teams and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Microsoft teams tools.

Can I manage the permissions and scopes for Microsoft teams while using Tool Router?

Yes, absolutely. You can configure which Microsoft teams scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Microsoft teams data and credentials are handled as safely as possible.

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