How to integrate Microsoft teams MCP with Pydantic AI

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Introduction

This guide walks you through connecting Microsoft teams to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Microsoft teams
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Microsoft teams workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Microsoft teams
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Microsoft teams
  • MCPServerStreamableHTTP connects to the Microsoft teams MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Microsoft teams
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["microsoft_teams"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Microsoft teams tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
microsoft_teams_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[microsoft_teams_mcp],
    instructions=(
        "You are a Microsoft teams assistant. Use Microsoft teams tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Microsoft teams endpoint
  • The agent uses GPT-5 to interpret user commands and perform Microsoft teams operations
  • The instructions field defines the agent's role and behavior

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Microsoft teams.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Microsoft teams API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Microsoft teams
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["microsoft_teams"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    microsoft_teams_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[microsoft_teams_mcp],
        instructions=(
            "You are a Microsoft teams assistant. Use Microsoft teams tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Microsoft teams.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Microsoft teams through Composio's Tool Router. With this setup, your agent can perform real Microsoft teams actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Microsoft teams for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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

CrewAI

CrewAI

Use Microsoft teams MCP with CrewAI

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 Pydantic AI?

Yes, you can. Pydantic AI 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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