Bring Your Agent to Teams
You've already built the agent. It lives somewhere: a LangChain chain, an Azure Foundry deployment, a Slack bot, a Next.js app. Your users live in Teams. Here's how to close that gap in under 50 lines.
It comes down to one pattern in the Teams TypeScript SDK: the HTTP server adapter. You plug it into your existing Express app, it registers a POST /api/messages route by default, and your existing server keeps running as-is. Nothing about your agent changes.
The SDK also handles the parts you don't want to think about: it verifies every incoming request is legitimately from Teams before invoking your handler, and routes messages to the right event handlers automatically.
A Python SDK is also available. The same adapter pattern applies with FastAPI and other ASGI frameworks. See Self-Managing Your Server in the Python docs.
The Pattern​
Every example in this post uses the same three-step shape:
import { App, ExpressAdapter } from '@microsoft/teams.apps';
const adapter = new ExpressAdapter(expressApp); // 1. wrap your server
const teamsApp = new App({ httpServerAdapter: adapter }); // 2. create the app
teamsApp.on('message', async ({ send, activity }) => { // 3. handle messages
await send(/* your agent's response */);
});
await teamsApp.initialize(); // registers POST /api/messages on your server
The SDK injects a POST /api/messages route into your existing Express app. Your server stays yours. The Teams SDK just adds one endpoint.
/api/messages is the default but not a requirement. You can configure the SDK to register any path as your messaging endpoint by passing a parameter to the App class.
Scenario 1: Slack Bot​
You have a Slack bot built with Bolt. Your team uses both Slack and Teams. Rather than maintaining two codebases, run both on the same Express server.
ExpressReceiver lets Bolt mount onto your Express app instead of owning the server. The Teams SDK does the same thing. One process, two platforms.
teams-app.ts:
import express from 'express';
import { App as BoltApp, ExpressReceiver } from '@slack/bolt';
import { App, ExpressAdapter } from '@microsoft/teams.apps';
const expressApp = express();
// Slack mounts at /slack/events
const slackReceiver = new ExpressReceiver({
signingSecret: process.env.SLACK_SIGNING_SECRET,
app: expressApp,
endpoints: { events: '/slack/events' },
});
const slackApp = new BoltApp({
token: process.env.SLACK_BOT_TOKEN,
receiver: slackReceiver,
});
slackApp.message('hello', async ({ say }) => {
await say('Hey! Caught you on Slack.');
});
// Teams mounts at /api/messages
const adapter = new ExpressAdapter(expressApp);
const teamsApp = new App({ httpServerAdapter: adapter });
teamsApp.on('message', async ({ send, activity }) => {
await send(`Hey ${activity.from.name}! You said: "${activity.text}"`);
});
export { expressApp, teamsApp };
Both platforms run in the same process. Slack hits /slack/events, Teams hits /api/messages, and any shared agent logic (LLM calls, database lookups, business rules) lives in plain functions that both handlers call.
Scenario 2: LangChain​
You have a LangChain chain. You want Teams users to talk to it.
chain.ts: existing LangChain logic, untouched
import { ChatOpenAI } from '@langchain/openai';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import { StringOutputParser } from '@langchain/core/output_parsers';
let _chain: ReturnType<typeof buildChain> | null = null;
function buildChain() {
const prompt = ChatPromptTemplate.fromMessages([
['system', 'You are a helpful assistant embedded in Microsoft Teams. Be concise.'],
['human', '{input}'],
]);
return prompt.pipe(new ChatOpenAI({ model: 'gpt-4o-mini' })).pipe(new StringOutputParser());
}
export function getChain() {
if (!_chain) _chain = buildChain();
return _chain;
}
teams-app.ts (the bridge):
import express from 'express';
import { App, ExpressAdapter } from '@microsoft/teams.apps';
import { getChain } from './chain';
const expressApp = express();
const adapter = new ExpressAdapter(expressApp);
const teamsApp = new App({ httpServerAdapter: adapter });
teamsApp.on('message', async ({ send, activity }) => {
await send({ type: 'typing' });
// pass the Teams message to LangChain
const reply = await getChain().invoke({ input: activity.text ?? '' });
await send(reply);
});
export { expressApp, teamsApp };
index.ts (start it):
import 'dotenv/config';
import http from 'http';
import { expressApp, teamsApp } from './teams-app';
await teamsApp.initialize();
http.createServer(expressApp).listen(3978);
Your chain runs on every message. The typing indicator fires before the LLM responds so users know something's happening.
Scenario 3: Azure AI Foundry​
You have an agent deployed in Azure AI Foundry. The Teams SDK gives you the message; you forward it to Foundry and relay the reply.
foundry-agent.ts
import { AIProjectClient } from '@azure/ai-projects';
import { DefaultAzureCredential } from '@azure/identity';
let _client: AIProjectClient | null = null;
function getClient() {
if (!_client) {
_client = AIProjectClient.fromEndpoint(
process.env.AZURE_AI_FOUNDRY_ENDPOINT!,
new DefaultAzureCredential(),
);
}
return _client;
}
export async function askFoundryAgent(userMessage: string): Promise<string> {
const client = getClient();
const thread = await client.agents.threads.create();
await client.agents.messages.create(thread.id, 'user', userMessage);
const run = await client.agents.runs.createAndPoll(
thread.id,
process.env.AZURE_AGENT_ID!,
);
if (run.status !== 'completed') throw new Error(`Run ended: ${run.status}`);
const messages = client.agents.messages.list(thread.id);
for await (const msg of messages) {
if (msg.role === 'assistant') {
return msg.content
.filter((c): c is { type: 'text'; text: { value: string } } => c.type === 'text')
.map((c) => c.text.value)
.join('');
}
}
return 'No response from agent.';
}
teams-app.ts:
import express from 'express';
import { App, ExpressAdapter } from '@microsoft/teams.apps';
import { askFoundryAgent } from './foundry-agent';
const expressApp = express();
const adapter = new ExpressAdapter(expressApp);
const teamsApp = new App({ httpServerAdapter: adapter });
teamsApp.on('message', async ({ send, activity }) => {
// pass the Teams message to Foundry
const reply = await askFoundryAgent(activity.text ?? '');
await send(reply);
});
export { expressApp, teamsApp };
Scenario 4: Next.js App​
You have a Next.js app and want a Teams bot alongside it (same deployment, same codebase). The App Router owns routing, so ExpressAdapter won't work. Instead, implement the IHttpServerAdapter interface to dispatch into a handler map that the Teams SDK populates.
The registerRoute stores the SDK's handler references when the app initializes; dispatch pulls the body and headers from the incoming request, looks up the right handler, and returns the response.
lib/nextjs-adapter.ts
import type { HttpMethod, IHttpServerAdapter, IHttpServerResponse, HttpRouteHandler } from '@microsoft/teams.apps';
export class NextjsAdapter implements IHttpServerAdapter {
private handlers = new Map<string, HttpRouteHandler>();
registerRoute(method: HttpMethod, path: string, handler: HttpRouteHandler): void {
this.handlers.set(`${method.toUpperCase()}:${path}`, handler);
}
async dispatch(method: string, path: string, body: unknown, headers: Record<string, string>): Promise<IHttpServerResponse> {
const handler = this.handlers.get(`${method.toUpperCase()}:${path}`);
if (!handler) return { status: 404, body: { error: 'Not found' } };
return handler({ body, headers });
}
}
lib/teams-app.ts:
import 'server-only';
import { App } from '@microsoft/teams.apps';
import { NextjsAdapter } from './nextjs-adapter';
const adapter = new NextjsAdapter();
const teamsApp = new App({ httpServerAdapter: adapter });
teamsApp.on('message', async ({ send, activity }) => {
await send(`Hello from Next.js! You said: "${activity.text}"`);
});
let initialized = false;
export async function getAdapter(): Promise<NextjsAdapter> {
if (!initialized) {
await teamsApp.initialize();
initialized = true;
}
return adapter;
}
app/api/messages/route.ts
import { NextRequest, NextResponse } from 'next/server';
import { getAdapter } from '@/lib/teams-app';
export async function POST(req: NextRequest): Promise<NextResponse> {
const adapter = await getAdapter();
const body = await req.json();
const headers: Record<string, string> = {};
req.headers.forEach((value, key) => { headers[key] = value; });
const result = await adapter.dispatch('POST', '/api/messages', body, headers);
const safeBody = result.body instanceof Error
? { error: result.body.message }
: result.body;
return NextResponse.json(safeBody, { status: result.status });
}
The Teams SDK doesn't care what's underneath. It just needs something that implements registerRoute and handles dispatch.
Registering Your Bot​
All four scenarios share the same registration step. First, get a public URL for your local server. Dev tunnels is the recommended option, or ngrok works too.
Then use the Teams SDK CLI to register your bot and write the credentials directly to your .env:
npm install -g @microsoft/teams.cli@preview
teams login
teams app create --name "My Bot" --endpoint https://your-tunnel-url/api/messages --env .env
One command handles AAD app registration, client secret generation, manifest creation, and bot setup. Your .env will be populated with CLIENT_ID, CLIENT_SECRET, and TENANT_ID automatically.
The same three lines, every time​
Every scenario in this post follows the same shape because the SDK is built around one idea: your server is yours. The adapter is the seam between your existing infrastructure and Teams. Whether you're running Express, a custom Next.js route, or your own adapter, the SDK doesn't care what's underneath. It just needs something that can register a route and handle a request.
const adapter = new <YourAdapter>(yourServer); // ExpressAdapter, NextjsAdapter, or your own
const teamsApp = new App({ httpServerAdapter: adapter });
teamsApp.on('message', async ({ send, activity }) => { /* your agent */ });
If you're already running a bot somewhere, wiring it into Teams is a few lines of glue code. Full docs at Self-Managing Your Server.