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Ms Teams Apps

  • 3 installs
  • 706 repo stars
  • Updated July 14, 2026
  • alinaqi/maggy

ms-teams-apps is a Claude Code skill for building Microsoft Teams bots and AI agents that integrate with LLMs like OpenAI and Claude, plus message extensions, tabs, Adaptive Cards, and the Graph API.

About

ms-teams-apps is a guidance skill for building AI-powered apps for Microsoft Teams, including conversational bots, message extensions, and tabs. It covers scaffolding a project with the Teams CLI, writing the app manifest, and wiring bots to LLMs like OpenAI and Claude using the Teams SDK v2 and Adaptive Cards. A developer uses it when building a Teams bot or agent that integrates with LLMs and the Graph API.

  • Build Microsoft Teams bots and AI agents wired to OpenAI or Claude
  • Covers the app manifest, message extensions, tabs, and Adaptive Cards
  • Uses Teams SDK v2 / M365 Agents SDK with the Teams CLI scaffolder

Ms Teams Apps by the numbers

  • 3 all-time installs (skills.sh)
  • Ranked #13,657 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

ms-teams-apps capabilities & compatibility

Requires an LLM API key (Azure OpenAI, OpenAI, or Claude) and a Microsoft Teams/365 environment.

Capabilities
chatbot · ai agent · message extension · adaptive cards
Works with
teams · openai · azure
Use cases
orchestration
Pricing
Bring your own API key
From the docs

What ms-teams-apps says it does

Microsoft Teams bots and AI agents - Claude/OpenAI, Adaptive Cards, Graph API
SKILL.md
**Purpose:** Build AI-powered agents and apps for Microsoft Teams. Create conversational bots, message extensions, and intelligent assistants that integrate with LLMs like OpenAI and Claude.
SKILL.md
npm install -g @microsoft/teams.cli
SKILL.md
npx skills add https://github.com/alinaqi/maggy --skill ms-teams-apps

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Listed on Skillselion
Installs3
repo stars706
Last updatedJuly 14, 2026
Repositoryalinaqi/maggy

What it does

Build an AI-powered Microsoft Teams bot, message extension, or tab wired to an LLM using the Teams SDK v2, Adaptive Cards, and the Graph API.

Who is it for?

Developers building conversational bots or AI agents inside Microsoft Teams.

Skip if: Chat integrations on platforms other than Microsoft Teams.

When should I use this skill?

When building Microsoft Teams bots, tabs, or message extensions.

What you get

A Teams app is scaffolded with a valid manifest and an AI bot wired to an LLM, with message extensions and Adaptive Cards.

  • Scaffolded Teams app with appPackage/manifest.json
  • AI bot handler wired to an LLM
  • Message extensions and Adaptive Cards

By the numbers

  • Four Teams app types: AI agents/bots, message extensions, tabs, webhooks/connectors
  • Manifest version 1.17

Files

SKILL.mdMarkdownGitHub ↗

Microsoft Teams Apps Skill

Purpose: Build AI-powered agents and apps for Microsoft Teams. Create conversational bots, message extensions, and intelligent assistants that integrate with LLMs like OpenAI and Claude.

---

Architecture Overview

┌─────────────────────────────────────────────────────────────────┐
│  TEAMS APP TYPES                                                 │
│  ─────────────────────────────────────────────────────────────  │
│                                                                 │
│  1. AI AGENTS (Bots)                                            │
│     Conversational apps powered by LLMs                         │
│     Handle messages, commands, and actions                      │
│                                                                 │
│  2. MESSAGE EXTENSIONS                                          │
│     Search external systems, insert cards into messages         │
│     Action commands with modal dialogs                          │
│                                                                 │
│  3. TABS                                                        │
│     Embedded web applications inside Teams                      │
│     Personal, channel, or meeting tabs                          │
│                                                                 │
│  4. WEBHOOKS & CONNECTORS                                       │
│     Incoming: Post messages to channels                         │
│     Outgoing: Respond to @mentions                              │
├─────────────────────────────────────────────────────────────────┤
│  SDK LANDSCAPE (2025)                                           │
│  ─────────────────────────────────────────────────────────────  │
│  Teams SDK v2: Primary SDK for Teams-only apps                  │
│  M365 Agents SDK: Multi-channel (Teams, Outlook, Copilot)       │
│  Teams Toolkit: VS Code extension for development               │
└─────────────────────────────────────────────────────────────────┘

---

Quick Start

Install Teams CLI

npm install -g @microsoft/teams.cli

Create New Project

# TypeScript (Recommended)
npx @microsoft/teams.cli new typescript my-agent --template echo

# Python
npx @microsoft/teams.cli new python my-agent --template echo

# C#
npx @microsoft/teams.cli new csharp my-agent --template echo

Project Structure

my-agent/
├── src/
│   ├── index.ts              # Entry point
│   ├── app.ts                # App configuration
│   └── handlers/
│       ├── message.ts        # Message handlers
│       └── commands.ts       # Command handlers
├── appPackage/
│   ├── manifest.json         # App manifest
│   ├── color.png             # App icon (192x192)
│   └── outline.png           # Outline icon (32x32)
├── .env                      # Environment variables
├── teamsapp.yml              # Teams Toolkit config
└── package.json

---

App Manifest

Basic Manifest Structure

{
  "$schema": "https://developer.microsoft.com/json-schemas/teams/v1.17/MicrosoftTeams.schema.json",
  "manifestVersion": "1.17",
  "version": "1.0.0",
  "id": "{{APP_ID}}",
  "developer": {
    "name": "Your Company",
    "websiteUrl": "https://yourcompany.com",
    "privacyUrl": "https://yourcompany.com/privacy",
    "termsOfUseUrl": "https://yourcompany.com/terms"
  },
  "name": {
    "short": "AI Assistant",
    "full": "AI Assistant for Teams"
  },
  "description": {
    "short": "Your AI-powered assistant",
    "full": "An intelligent assistant that helps you with tasks using AI."
  },
  "icons": {
    "color": "color.png",
    "outline": "outline.png"
  },
  "accentColor": "#5558AF",
  "bots": [
    {
      "botId": "{{BOT_ID}}",
      "scopes": ["personal", "team", "groupChat"],
      "supportsFiles": false,
      "isNotificationOnly": false,
      "commandLists": [
        {
          "scopes": ["personal", "team", "groupChat"],
          "commands": [
            {
              "title": "help",
              "description": "Show available commands"
            },
            {
              "title": "ask",
              "description": "Ask the AI a question"
            }
          ]
        }
      ]
    }
  ],
  "permissions": ["identity", "messageTeamMembers"],
  "validDomains": ["*.azurewebsites.net"]
}

Manifest with Message Extensions

{
  "composeExtensions": [
    {
      "botId": "{{BOT_ID}}",
      "commands": [
        {
          "id": "searchQuery",
          "type": "query",
          "title": "Search",
          "description": "Search for information",
          "initialRun": true,
          "parameters": [
            {
              "name": "query",
              "title": "Search query",
              "description": "Enter your search terms",
              "inputType": "text"
            }
          ]
        },
        {
          "id": "createTask",
          "type": "action",
          "title": "Create Task",
          "description": "Create a new task",
          "fetchTask": true,
          "context": ["compose", "commandBox", "message"]
        }
      ]
    }
  ]
}

---

AI Agent Development

Basic Bot with Teams SDK v2

// src/app.ts
import { App, HttpPlugin, DevtoolsPlugin } from '@microsoft/teams.ai';
import { OpenAIModel, ActionPlanner, PromptManager } from '@microsoft/teams.ai';

// Configure the AI model
const model = new OpenAIModel({
  azureApiKey: process.env.AZURE_OPENAI_API_KEY!,
  azureDefaultDeployment: process.env.AZURE_OPENAI_DEPLOYMENT!,
  azureEndpoint: process.env.AZURE_OPENAI_ENDPOINT!,
  // Or use OpenAI directly:
  // apiKey: process.env.OPENAI_API_KEY!,
  // defaultModel: 'gpt-4'
});

// Configure prompts
const prompts = new PromptManager({
  promptsFolder: './src/prompts'
});

// Create action planner
const planner = new ActionPlanner({
  model,
  prompts,
  defaultPrompt: 'chat'
});

// Create the app
const app = new App({
  plugins: [
    new HttpPlugin(),
    new DevtoolsPlugin()
  ],
  ai: {
    planner
  }
});

// Handle messages
app.on('message', async (context, state) => {
  // AI automatically handles the conversation
  // The planner uses the 'chat' prompt to generate responses
});

// Handle specific commands
app.message('/help', async (context, state) => {
  await context.sendActivity({
    type: 'message',
    text: 'Available commands:\n- /help - Show this message\n- /ask [question] - Ask me anything'
  });
});

// Start the app
app.start();

Prompt Configuration

# src/prompts/chat/config.json
{
  "schema": 1.1,
  "description": "AI Assistant for Teams",
  "type": "completion",
  "completion": {
    "model": "gpt-4",
    "max_tokens": 1000,
    "temperature": 0.7,
    "top_p": 1
  }
}
# src/prompts/chat/skprompt.txt
You are an AI assistant for Microsoft Teams. You help users with their questions and tasks.

Current conversation:
{{$history}}

User: {{$input}}
Assistant:

---

Integrating Claude/Anthropic

Claude-Powered Teams Bot

// src/claude-bot.ts
import { App, HttpPlugin } from '@microsoft/teams.ai';
import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY!
});

const app = new App({
  plugins: [new HttpPlugin()]
});

// Conversation history store
const conversations = new Map<string, Anthropic.MessageParam[]>();

app.on('message', async (context, state) => {
  const userId = context.activity.from.id;
  const userMessage = context.activity.text;

  // Get or initialize conversation history
  if (!conversations.has(userId)) {
    conversations.set(userId, []);
  }
  const history = conversations.get(userId)!;

  // Add user message to history
  history.push({ role: 'user', content: userMessage });

  // Show typing indicator
  await context.sendActivity({ type: 'typing' });

  try {
    // Call Claude API
    const response = await anthropic.messages.create({
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      system: `You are an AI assistant integrated into Microsoft Teams.
        Help users with their questions and tasks.
        Be concise and helpful. Use markdown formatting when appropriate.
        Current user: ${context.activity.from.name}`,
      messages: history
    });

    const assistantMessage = response.content[0].type === 'text'
      ? response.content[0].text
      : '';

    // Add assistant response to history
    history.push({ role: 'assistant', content: assistantMessage });

    // Keep history manageable (last 20 messages)
    if (history.length > 20) {
      history.splice(0, history.length - 20);
    }

    // Send response
    await context.sendActivity({
      type: 'message',
      text: assistantMessage
    });

  } catch (error) {
    console.error('Claude API error:', error);
    await context.sendActivity({
      type: 'message',
      text: 'Sorry, I encountered an error processing your request.'
    });
  }
});

// Clear conversation command
app.message('/clear', async (context, state) => {
  const userId = context.activity.from.id;
  conversations.delete(userId);
  await context.sendActivity('Conversation cleared. Starting fresh!');
});

app.start();

Claude with Tools/Function Calling

// src/claude-agent.ts
import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic();

// Define tools the agent can use
const tools: Anthropic.Tool[] = [
  {
    name: 'search_knowledge_base',
    description: 'Search the company knowledge base for information',
    input_schema: {
      type: 'object' as const,
      properties: {
        query: {
          type: 'string',
          description: 'The search query'
        }
      },
      required: ['query']
    }
  },
  {
    name: 'create_task',
    description: 'Create a new task in the task management system',
    input_schema: {
      type: 'object' as const,
      properties: {
        title: { type: 'string', description: 'Task title' },
        description: { type: 'string', description: 'Task description' },
        assignee: { type: 'string', description: 'Person to assign the task to' },
        due_date: { type: 'string', description: 'Due date in YYYY-MM-DD format' }
      },
      required: ['title']
    }
  },
  {
    name: 'get_calendar',
    description: 'Get calendar events for a user',
    input_schema: {
      type: 'object' as const,
      properties: {
        user: { type: 'string', description: 'User email or name' },
        days: { type: 'number', description: 'Number of days to look ahead' }
      },
      required: ['user']
    }
  }
];

// Tool implementations
async function executeTools(toolName: string, toolInput: any): Promise<string> {
  switch (toolName) {
    case 'search_knowledge_base':
      // Implement your search logic
      return `Found 3 results for "${toolInput.query}":\n1. Document A\n2. Document B\n3. Document C`;

    case 'create_task':
      // Implement task creation (e.g., call Microsoft Graph API)
      return `Task created: "${toolInput.title}"`;

    case 'get_calendar':
      // Implement calendar lookup
      return `Calendar for ${toolInput.user}: 2 meetings today`;

    default:
      return 'Unknown tool';
  }
}

// Agent loop with tool use
async function runAgent(userMessage: string): Promise<string> {
  let messages: Anthropic.MessageParam[] = [
    { role: 'user', content: userMessage }
  ];

  while (true) {
    const response = await anthropic.messages.create({
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      system: 'You are a helpful Teams assistant. Use tools when needed to help users.',
      tools,
      messages
    });

    // Check if we need to use tools
    if (response.stop_reason === 'tool_use') {
      const toolResults: Anthropic.MessageParam[] = [];

      for (const content of response.content) {
        if (content.type === 'tool_use') {
          const result = await executeTools(content.name, content.input);
          toolResults.push({
            role: 'user',
            content: [{
              type: 'tool_result',
              tool_use_id: content.id,
              content: result
            }]
          });
        }
      }

      messages.push({ role: 'assistant', content: response.content });
      messages.push(...toolResults);
      continue;
    }

    // Return final text response
    const textContent = response.content.find(c => c.type === 'text');
    return textContent?.text || 'No response';
  }
}

---

Adaptive Cards

Basic Adaptive Card

// src/cards/welcome-card.ts
import { CardFactory } from 'botbuilder';

export function createWelcomeCard(userName: string) {
  return CardFactory.adaptiveCard({
    type: 'AdaptiveCard',
    $schema: 'http://adaptivecards.io/schemas/adaptive-card.json',
    version: '1.5',
    body: [
      {
        type: 'TextBlock',
        text: `Welcome, ${userName}!`,
        size: 'Large',
        weight: 'Bolder'
      },
      {
        type: 'TextBlock',
        text: 'I\'m your AI assistant. How can I help you today?',
        wrap: true
      },
      {
        type: 'ActionSet',
        actions: [
          {
            type: 'Action.Submit',
            title: 'Get Started',
            data: { action: 'getStarted' }
          },
          {
            type: 'Action.Submit',
            title: 'View Help',
            data: { action: 'help' }
          }
        ]
      }
    ]
  });
}

AI Response Card with Actions

// src/cards/ai-response-card.ts
export function createAIResponseCard(
  question: string,
  answer: string,
  sources?: string[]
) {
  return {
    type: 'AdaptiveCard',
    $schema: 'http://adaptivecards.io/schemas/adaptive-card.json',
    version: '1.5',
    body: [
      {
        type: 'Container',
        style: 'emphasis',
        items: [
          {
            type: 'TextBlock',
            text: 'Your Question',
            size: 'Small',
            weight: 'Bolder'
          },
          {
            type: 'TextBlock',
            text: question,
            wrap: true
          }
        ]
      },
      {
        type: 'Container',
        items: [
          {
            type: 'TextBlock',
            text: 'AI Response',
            size: 'Small',
            weight: 'Bolder'
          },
          {
            type: 'TextBlock',
            text: answer,
            wrap: true
          }
        ]
      },
      ...(sources && sources.length > 0 ? [{
        type: 'Container',
        items: [
          {
            type: 'TextBlock',
            text: 'Sources',
            size: 'Small',
            weight: 'Bolder'
          },
          ...sources.map(source => ({
            type: 'TextBlock',
            text: `• ${source}`,
            size: 'Small'
          }))
        ]
      }] : [])
    ],
    actions: [
      {
        type: 'Action.Submit',
        title: '👍 Helpful',
        data: { action: 'feedback', value: 'positive' }
      },
      {
        type: 'Action.Submit',
        title: '👎 Not Helpful',
        data: { action: 'feedback', value: 'negative' }
      },
      {
        type: 'Action.Submit',
        title: 'Ask Follow-up',
        data: { action: 'followUp' }
      }
    ]
  };
}

Form Card for User Input

// src/cards/task-form-card.ts
export function createTaskFormCard() {
  return {
    type: 'AdaptiveCard',
    $schema: 'http://adaptivecards.io/schemas/adaptive-card.json',
    version: '1.5',
    body: [
      {
        type: 'TextBlock',
        text: 'Create New Task',
        size: 'Large',
        weight: 'Bolder'
      },
      {
        type: 'Input.Text',
        id: 'taskTitle',
        label: 'Task Title',
        isRequired: true,
        placeholder: 'Enter task title'
      },
      {
        type: 'Input.Text',
        id: 'taskDescription',
        label: 'Description',
        isMultiline: true,
        placeholder: 'Enter task description'
      },
      {
        type: 'Input.ChoiceSet',
        id: 'priority',
        label: 'Priority',
        choices: [
          { title: 'High', value: 'high' },
          { title: 'Medium', value: 'medium' },
          { title: 'Low', value: 'low' }
        ],
        value: 'medium'
      },
      {
        type: 'Input.Date',
        id: 'dueDate',
        label: 'Due Date'
      }
    ],
    actions: [
      {
        type: 'Action.Submit',
        title: 'Create Task',
        data: { action: 'createTask' }
      },
      {
        type: 'Action.Submit',
        title: 'Cancel',
        data: { action: 'cancel' }
      }
    ]
  };
}

---

Microsoft Graph Integration

Setup Graph Client

// src/graph/client.ts
import { Client } from '@microsoft/microsoft-graph-client';
import { TokenCredentialAuthenticationProvider } from '@microsoft/microsoft-graph-client/authProviders/azureTokenCredentials';
import { ClientSecretCredential } from '@azure/identity';

export function createGraphClient() {
  const credential = new ClientSecretCredential(
    process.env.AZURE_TENANT_ID!,
    process.env.AZURE_CLIENT_ID!,
    process.env.AZURE_CLIENT_SECRET!
  );

  const authProvider = new TokenCredentialAuthenticationProvider(credential, {
    scopes: ['https://graph.microsoft.com/.default']
  });

  return Client.initWithMiddleware({ authProvider });
}

Common Graph Operations

// src/graph/operations.ts
import { Client } from '@microsoft/microsoft-graph-client';

export class GraphOperations {
  constructor(private client: Client) {}

  // Get user profile
  async getUserProfile(userId: string) {
    return this.client.api(`/users/${userId}`).get();
  }

  // Get user's calendar events
  async getCalendarEvents(userId: string, days: number = 7) {
    const startDate = new Date().toISOString();
    const endDate = new Date(Date.now() + days * 24 * 60 * 60 * 1000).toISOString();

    return this.client
      .api(`/users/${userId}/calendarView`)
      .query({
        startDateTime: startDate,
        endDateTime: endDate
      })
      .select('subject,start,end,location')
      .orderby('start/dateTime')
      .get();
  }

  // Send email
  async sendEmail(
    fromUserId: string,
    to: string,
    subject: string,
    body: string
  ) {
    return this.client.api(`/users/${fromUserId}/sendMail`).post({
      message: {
        subject,
        body: { contentType: 'HTML', content: body },
        toRecipients: [{ emailAddress: { address: to } }]
      }
    });
  }

  // Create Teams meeting
  async createMeeting(
    userId: string,
    subject: string,
    startTime: string,
    endTime: string,
    attendees: string[]
  ) {
    return this.client.api(`/users/${userId}/onlineMeetings`).post({
      subject,
      startDateTime: startTime,
      endDateTime: endTime,
      participants: {
        attendees: attendees.map(email => ({
          upn: email,
          role: 'attendee'
        }))
      }
    });
  }

  // Post message to channel
  async postToChannel(teamId: string, channelId: string, message: string) {
    return this.client
      .api(`/teams/${teamId}/channels/${channelId}/messages`)
      .post({
        body: { content: message }
      });
  }
}

---

Authentication

SSO with Teams SDK

// src/auth.ts
import { App } from '@microsoft/teams.ai';

const app = new App({
  // ... other config
});

app.on('message', async ({ userGraph, isSignedIn, send, signin }) => {
  // Check if user is signed in
  if (!isSignedIn) {
    // Initiate sign-in flow
    await signin();
    return;
  }

  // User is signed in, access Graph API
  const me = await userGraph.call({
    method: 'GET',
    path: '/me'
  });

  await send(`Hello, ${me.displayName}!`);
});

Manual OAuth Flow

// src/auth/oauth.ts
import { OAuthPrompt, OAuthPromptSettings } from 'botbuilder-dialogs';

const oauthSettings: OAuthPromptSettings = {
  connectionName: process.env.OAUTH_CONNECTION_NAME!,
  text: 'Please sign in to continue',
  title: 'Sign In',
  timeout: 300000 // 5 minutes
};

// In your dialog
async function handleAuth(context, state) {
  const tokenResponse = await context.adapter.getUserToken(
    context,
    oauthSettings.connectionName
  );

  if (!tokenResponse?.token) {
    // No token, show sign-in card
    await context.sendActivity({
      attachments: [
        CardFactory.oauthCard(
          oauthSettings.connectionName,
          oauthSettings.title,
          oauthSettings.text
        )
      ]
    });
    return null;
  }

  return tokenResponse.token;
}

---

RAG (Retrieval-Augmented Generation)

Vector Search with Azure AI Search

// src/rag/azure-search.ts
import { SearchClient, AzureKeyCredential } from '@azure/search-documents';

const searchClient = new SearchClient(
  process.env.AZURE_SEARCH_ENDPOINT!,
  process.env.AZURE_SEARCH_INDEX!,
  new AzureKeyCredential(process.env.AZURE_SEARCH_KEY!)
);

export async function searchKnowledgeBase(
  query: string,
  topK: number = 5
): Promise<string[]> {
  const results = await searchClient.search(query, {
    top: topK,
    select: ['content', 'title', 'source'],
    queryType: 'semantic',
    semanticConfiguration: 'default'
  });

  const documents: string[] = [];
  for await (const result of results.results) {
    documents.push(`${result.document.title}: ${result.document.content}`);
  }

  return documents;
}

RAG-Enhanced Claude Response

// src/rag/claude-rag.ts
import Anthropic from '@anthropic-ai/sdk';
import { searchKnowledgeBase } from './azure-search';

const anthropic = new Anthropic();

export async function getRAGResponse(userQuery: string): Promise<string> {
  // 1. Search knowledge base
  const relevantDocs = await searchKnowledgeBase(userQuery);

  // 2. Build context
  const context = relevantDocs.join('\n\n---\n\n');

  // 3. Generate response with context
  const response = await anthropic.messages.create({
    model: 'claude-sonnet-4-20250514',
    max_tokens: 1024,
    system: `You are a helpful assistant for Teams. Answer questions based on the provided context.
If the context doesn't contain relevant information, say so and provide a general response.
Always cite your sources when using information from the context.`,
    messages: [
      {
        role: 'user',
        content: `Context:\n${context}\n\nQuestion: ${userQuery}`
      }
    ]
  });

  return response.content[0].type === 'text' ? response.content[0].text : '';
}

---

Deployment

Azure Bot Service Setup

# Create resource group
az group create --name rg-teams-bot --location eastus

# Create App Service plan
az appservice plan create \
  --name asp-teams-bot \
  --resource-group rg-teams-bot \
  --sku B1 \
  --is-linux

# Create Web App
az webapp create \
  --name my-teams-bot \
  --resource-group rg-teams-bot \
  --plan asp-teams-bot \
  --runtime "NODE:18-lts"

# Create Bot Channels Registration
az bot create \
  --resource-group rg-teams-bot \
  --name my-teams-bot \
  --kind registration \
  --endpoint https://my-teams-bot.azurewebsites.net/api/messages \
  --sku F0

# Enable Teams channel
az bot msteams create \
  --name my-teams-bot \
  --resource-group rg-teams-bot

Environment Variables

# .env
# Azure Bot
BOT_ID=your-bot-id
BOT_PASSWORD=your-bot-password
BOT_TENANT_ID=your-tenant-id

# Azure OpenAI
AZURE_OPENAI_API_KEY=your-key
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
AZURE_OPENAI_DEPLOYMENT=gpt-4

# Or OpenAI
OPENAI_API_KEY=sk-xxx

# Or Anthropic
ANTHROPIC_API_KEY=sk-ant-xxx

# Microsoft Graph
AZURE_CLIENT_ID=your-client-id
AZURE_CLIENT_SECRET=your-client-secret
AZURE_TENANT_ID=your-tenant-id

# Azure AI Search (for RAG)
AZURE_SEARCH_ENDPOINT=https://your-search.search.windows.net
AZURE_SEARCH_KEY=your-key
AZURE_SEARCH_INDEX=knowledge-base

Docker Deployment

# Dockerfile
FROM node:18-alpine

WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY . .
RUN npm run build

EXPOSE 3978

CMD ["node", "dist/index.js"]
# docker-compose.yml
version: '3.8'

services:
  teams-bot:
    build: .
    ports:
      - "3978:3978"
    environment:
      - BOT_ID=${BOT_ID}
      - BOT_PASSWORD=${BOT_PASSWORD}
      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
    restart: unless-stopped

Teams Toolkit Deployment

# Login to Azure
npx teamsfx account login azure

# Provision resources
npx teamsfx provision --env dev

# Deploy
npx teamsfx deploy --env dev

# Publish to Teams
npx teamsfx publish --env dev

---

Testing

Local Testing with ngrok

# Start ngrok tunnel
ngrok http 3978

# Update manifest with ngrok URL
# Bot endpoint: https://xxxx.ngrok.io/api/messages

Teams Toolkit Local Debug

# Start local debugging (opens Teams with your app)
npx teamsfx preview --local

Unit Testing

// tests/bot.test.ts
import { TestAdapter, TurnContext } from 'botbuilder';
import { createWelcomeCard } from '../src/cards/welcome-card';

describe('Bot Tests', () => {
  let adapter: TestAdapter;

  beforeEach(() => {
    adapter = new TestAdapter();
  });

  test('should respond to hello', async () => {
    await adapter
      .send('hello')
      .assertReply((activity) => {
        expect(activity.text).toContain('Hello');
      });
  });

  test('should create welcome card', () => {
    const card = createWelcomeCard('John');
    expect(card.content.body[0].text).toContain('John');
  });
});

---

Best Practices

Conversation Design

┌─────────────────────────────────────────────────────────────────┐
│  CONVERSATION UX GUIDELINES                                     │
│  ─────────────────────────────────────────────────────────────  │
│                                                                 │
│  1. GREET INTELLIGENTLY                                         │
│     - Welcome new users with onboarding card                    │
│     - Return users get quick access to recent actions           │
│                                                                 │
│  2. HANDLE ERRORS GRACEFULLY                                    │
│     - Never show stack traces to users                          │
│     - Provide clear recovery options                            │
│     - Log errors for debugging                                  │
│                                                                 │
│  3. USE CARDS FOR RICH CONTENT                                  │
│     - Adaptive Cards for forms and structured data              │
│     - Hero Cards for simple actions                             │
│     - Keep cards concise and actionable                         │
│                                                                 │
│  4. TYPING INDICATORS                                           │
│     - Show typing for long operations                           │
│     - Provide progress updates for very long tasks              │
│                                                                 │
│  5. CONTEXT AWARENESS                                           │
│     - Remember conversation history                             │
│     - Personalize based on user preferences                     │
│     - Respect team/channel context                              │
└─────────────────────────────────────────────────────────────────┘

Security Checklist

  • [ ] Validate all incoming messages
  • [ ] Use App-Only auth for Graph API when possible
  • [ ] Never log sensitive user data
  • [ ] Implement rate limiting
  • [ ] Use managed identity in Azure
  • [ ] Rotate secrets regularly
  • [ ] Enable audit logging

Performance Tips

TipDescription
Cache Graph tokensToken refresh is expensive
Stream long responsesUse typing indicator + chunked responses
Index knowledge basePre-embed documents for RAG
Use connection poolingReuse HTTP connections
Compress payloadsGzip large card responses

---

Project Templates

AI Assistant Template

// Complete AI assistant with Claude
import { App, HttpPlugin } from '@microsoft/teams.ai';
import Anthropic from '@anthropic-ai/sdk';
import { createWelcomeCard } from './cards/welcome-card';
import { createAIResponseCard } from './cards/ai-response-card';

const anthropic = new Anthropic();
const app = new App({ plugins: [new HttpPlugin()] });
const conversations = new Map<string, Anthropic.MessageParam[]>();

// Welcome new users
app.conversationUpdate('membersAdded', async (context) => {
  for (const member of context.activity.membersAdded || []) {
    if (member.id !== context.activity.recipient.id) {
      await context.sendActivity({
        attachments: [createWelcomeCard(member.name || 'User')]
      });
    }
  }
});

// Handle messages
app.on('message', async (context) => {
  const userId = context.activity.from.id;
  const userMessage = context.activity.text;

  // Initialize or get conversation
  if (!conversations.has(userId)) {
    conversations.set(userId, []);
  }
  const history = conversations.get(userId)!;
  history.push({ role: 'user', content: userMessage });

  // Show typing
  await context.sendActivity({ type: 'typing' });

  // Get AI response
  const response = await anthropic.messages.create({
    model: 'claude-sonnet-4-20250514',
    max_tokens: 1024,
    system: 'You are a helpful Teams assistant.',
    messages: history
  });

  const answer = response.content[0].type === 'text'
    ? response.content[0].text
    : '';

  history.push({ role: 'assistant', content: answer });

  // Send rich card response
  await context.sendActivity({
    attachments: [{
      contentType: 'application/vnd.microsoft.card.adaptive',
      content: createAIResponseCard(userMessage, answer)
    }]
  });
});

// Handle card actions
app.on('adaptiveCard/action', async (context) => {
  const action = context.activity.value?.action;

  switch (action) {
    case 'feedback':
      // Log feedback
      console.log('Feedback:', context.activity.value);
      await context.sendActivity('Thanks for your feedback!');
      break;
    case 'followUp':
      await context.sendActivity('What would you like to know more about?');
      break;
  }
});

app.start();

---

Troubleshooting

IssueCauseFix
Bot not respondingEndpoint unreachableCheck ngrok/Azure URL in manifest
Auth failuresToken expired/invalidRefresh OAuth connection
Cards not renderingInvalid schemaValidate at adaptivecards.io/designer
Graph 403 errorsMissing permissionsCheck app registration permissions
Slow responsesAPI latencyAdd typing indicator, consider streaming

---

Resources

Related skills

FAQ

Which SDK does it use?

Teams SDK v2 for Teams-only apps and the M365 Agents SDK for multi-channel (Teams, Outlook, Copilot), scaffolded via the Teams CLI.

Which LLMs are supported?

The skill wires bots to LLMs like OpenAI (including Azure OpenAI) and Claude.

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