> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Microsoft Teams Integration

> Technical design for PraisonAI Microsoft Teams channel implementation

Run PraisonAI agents in Microsoft Teams channels via BotOS — enterprise collaboration with the same agent brain as Telegram and Discord.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
import os
from praisonaiagents import Agent
from praisonai.bots import Bot

agent = Agent(
    name="Teams Assistant",
    instructions="Help users in Microsoft Teams channels.",
)

bot = Bot(
    "teams",
    agent=agent,
    app_id=os.getenv("TEAMS_APP_ID"),
    app_password=os.getenv("TEAMS_APP_PASSWORD"),
)
bot.run()
```

The user messages in Microsoft Teams; BotOS routes the conversation to the same agent used on other channels.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    A[Agent] --> B[Teams Bot]
    B --> C[Bot Framework]
    C --> D[Microsoft Teams]

    classDef agent fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef tool fill:#189AB4,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff

    class A agent
    class B,C tool
    class D output
```

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant User
    participant Agent
    participant Feature as Microsoft Teams Integration

    User->>Agent: Request
    Agent->>Feature: Process request
    Feature-->>Agent: Result    Agent-->>User: Response
```

## Quick Start

<Steps>
  <Step title="Simple Usage">
    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    import os
    from praisonaiagents import Agent
    from praisonai.bots import Bot

    agent = Agent(
        name="Teams Assistant",
        instructions="Help users in Microsoft Teams channels.",
    )

    bot = Bot(
        "teams",
        agent=agent,
        app_id=os.getenv("TEAMS_APP_ID"),
        app_password=os.getenv("TEAMS_APP_PASSWORD"),
    )
    bot.run()
    ```
  </Step>

  <Step title="With Configuration">
    Add Teams to a multi-platform BotOS setup:

    ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
    import os
    from praisonaiagents import Agent
    from praisonai.bots import BotOS

    agent = Agent(name="Assistant", instructions="Be helpful.")

    botos = BotOS(
        agent=agent,
        platforms={
            "teams": {
                "app_id": os.getenv("TEAMS_APP_ID"),
                "app_password": os.getenv("TEAMS_APP_PASSWORD"),
                "tenant_id": os.getenv("AZURE_TENANT_ID"),
            },
        },
    )
    botos.run()
    ```
  </Step>
</Steps>

<Info>
  **RFC Status**: Draft | **Priority**: High | **Timeline**: Q2 2026
</Info>

***

## Overview

This RFC proposes Microsoft Teams as a first-class PraisonAI messaging channel for enterprise RFPs and Microsoft 365-first organisations.

### Success Criteria

* Full BotOS protocol compatibility
* Multi-agent deployment in Teams channels
* Enterprise security and compliance features
* Rich message formatting and adaptive cards
* SSO and Azure AD integration

***

## Architecture

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph TB
    A[Agent] --> B[TeamsBot]
    B --> C[Bot Framework SDK]
    C --> D[Teams API]
    D --> E[Microsoft Teams]
    F[Azure AD] --> B

    classDef agent fill:#8B0000,color:#fff
    classDef tool fill:#189AB4,color:#fff

    class A,E agent
    class B,C,D,F tool
```

***

## Configuration

```yaml theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# teams-bot.yaml
platform: teams
app_id: ${TEAMS_APP_ID}
app_password: ${TEAMS_APP_PASSWORD}
tenant_id: ${AZURE_TENANT_ID}

agent:
  name: TeamsAssistant
  instructions: You are a helpful assistant in Microsoft Teams

features:
  adaptive_cards: true
  file_uploads: true
  threading: true

security:
  sso_enabled: true
  audit_logging: true
```

***

## Implementation Plan

| Phase                 | Duration | Scope                                           |
| --------------------- | -------- | ----------------------------------------------- |
| 1 — Core Messaging    | 4 weeks  | Bot Framework SDK, send/receive, BotOS protocol |
| 2 — Advanced Features | 3 weeks  | Adaptive cards, Azure AD, audit logging         |
| 3 — Production        | 2 weeks  | Test suite, security audit, documentation       |

***

## Security

<Warning>
  Enterprise deployments require audit logging, encryption in transit and at rest, and GDPR/CCPA compliance for EU/CA tenants.
</Warning>

| Layer          | Implementation                 |
| -------------- | ------------------------------ |
| Authentication | Azure AD OAuth 2.0             |
| Encryption     | TLS 1.3 + Azure Key Vault      |
| Audit trail    | Azure Monitor + PraisonAI logs |
| Rate limiting  | Azure API Management           |

***

## Best Practices

<AccordionGroup>
  <Accordion title="Use Azure Key Vault for credentials">
    Store `TEAMS_APP_ID` and `TEAMS_APP_PASSWORD` in Key Vault — never commit secrets to source control.
  </Accordion>

  <Accordion title="Deploy AgentTeam across channels">
    Use `AgentTeam` for multi-agent Teams channels with session management per conversation.
  </Accordion>

  <Accordion title="Enable SSO for enterprise tenants">
    Configure Azure AD SSO so users authenticate with existing Microsoft 365 credentials.
  </Accordion>

  <Accordion title="Use adaptive cards for approvals">
    Human-in-the-loop workflows map cleanly to Teams adaptive card submit actions.
  </Accordion>
</AccordionGroup>

***

## Related

<CardGroup cols={2}>
  <Card title="Messaging Channels Strategy" icon="users-gear" href="/docs/features/messaging-channels-strategy">
    Overall messaging platform roadmap
  </Card>

  <Card title="Agent Server" icon="server" href="/docs/features/agent-server">
    Deploy agents with HTTP APIs
  </Card>
</CardGroup>

<Info>
  **Review & Feedback**: Comment on GitHub issue #1311 with questions or suggestions.
</Info>