M3

m365-agents-ts

A TypeScript SDK for developing and hosting enterprise agents on the Microsoft 365 ecosystem.

Install

mkdir -p .claude/skills/m365-agents-ts && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/9764" && unzip -o skill.zip -d .claude/skills/m365-agents-ts && rm skill.zip

Installs to .claude/skills/m365-agents-ts

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Microsoft 365 Agents SDK for TypeScript/Node.js.
48 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Host agents using Express
  • Route agent activities
  • Stream responses via Azure OpenAI
  • Integrate with Copilot Studio

How it works

The skill provides an Express-based framework for building agents that handle activities, route messages, and stream AI-generated responses.

Inputs & outputs

You give it
Agent requirement or chat prompt
You get back
Streaming agent response

When to use m365-agents-ts

  • Create a new Microsoft 365 agent using Express
  • Implement streaming chat responses with Azure OpenAI
  • Configure Copilot Studio integration credentials

About this skill

Microsoft 365 Agents SDK (TypeScript)

Build enterprise agents for Microsoft 365, Teams, and Copilot Studio using the Microsoft 365 Agents SDK with Express hosting, AgentApplication routing, streaming responses, and Copilot Studio client integrations.

Before implementation

  • Use the microsoft-docs MCP to verify the latest API signatures for AgentApplication, startServer, and CopilotStudioClient.
  • Confirm package versions on npm before wiring up samples or templates.

Installation

npm install @microsoft/agents-hosting @microsoft/agents-hosting-express @microsoft/agents-activity
npm install @microsoft/agents-copilotstudio-client

Environment Variables

PORT=3978
AZURE_RESOURCE_NAME=<azure-openai-resource>
AZURE_API_KEY=<azure-openai-key>
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o-mini

TENANT_ID=<tenant-id>
CLIENT_ID=<client-id>
CLIENT_SECRET=<client-secret>

COPILOT_ENVIRONMENT_ID=<environment-id>
COPILOT_SCHEMA_NAME=<schema-name>
COPILOT_CLIENT_ID=<copilot-app-client-id>
COPILOT_BEARER_TOKEN=<copilot-jwt>

Core Workflow: Express-hosted AgentApplication

import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";
import { startServer } from "@microsoft/agents-hosting-express";

const agent = new AgentApplication<TurnState>();

agent.onConversationUpdate("membersAdded", async (context: TurnContext) => {
  await context.sendActivity("Welcome to the agent.");
});

agent.onMessage("hello", async (context: TurnContext) => {
  await context.sendActivity(`Echo: ${context.activity.text}`);
});

startServer(agent);

Streaming responses with Azure OpenAI

import { azure } from "@ai-sdk/azure";
import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";
import { startServer } from "@microsoft/agents-hosting-express";
import { streamText } from "ai";

const agent = new AgentApplication<TurnState>();

agent.onMessage("poem", async (context: TurnContext) => {
  context.streamingResponse.setFeedbackLoop(true);
  context.streamingResponse.setGeneratedByAILabel(true);
  context.streamingResponse.setSensitivityLabel({
    type: "https://schema.org/Message",
    "@type": "CreativeWork",
    name: "Internal",
  });

  await context.streamingResponse.queueInformativeUpdate("starting a poem...");

  const { fullStream } = streamText({
    model: azure(process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "gpt-4o-mini"),
    system: "You are a creative assistant.",
    prompt: "Write a poem about Apollo.",
  });

  try {
    for await (const part of fullStream) {
      if (part.type === "text-delta" && part.text.length > 0) {
        await context.streamingResponse.queueTextChunk(part.text);
      }
      if (part.type === "error") {
        throw new Error(`Streaming error: ${part.error}`);
      }
    }
  } finally {
    await context.streamingResponse.endStream();
  }
});

startServer(agent);

Invoke activity handling

import { Activity, ActivityTypes } from "@microsoft/agents-activity";
import { AgentApplication, TurnContext, TurnState } from "@microsoft/agents-hosting";

const agent = new AgentApplication<TurnState>();

agent.onActivity("invoke", async (context: TurnContext) => {
  const invokeResponse = Activity.fromObject({
    type: ActivityTypes.InvokeResponse,
    value: { status: 200 },
  });

  await context.sendActivity(invokeResponse);
  await context.sendActivity("Thanks for submitting your feedback.");
});

Copilot Studio client (Direct to Engine)

import { CopilotStudioClient } from "@microsoft/agents-copilotstudio-client";

const settings = {
  environmentId: process.env.COPILOT_ENVIRONMENT_ID!,
  schemaName: process.env.COPILOT_SCHEMA_NAME!,
  clientId: process.env.COPILOT_CLIENT_ID!,
};

const tokenProvider = async (): Promise<string> => {
  return process.env.COPILOT_BEARER_TOKEN!;
};

const client = new CopilotStudioClient(settings, tokenProvider);

const conversation = await client.startConversationAsync();
const reply = await client.askQuestionAsync("Hello!", conversation.id);
console.log(reply);

Copilot Studio WebChat integration

import { CopilotStudioWebChat } from "@microsoft/agents-copilotstudio-client";

const directLine = CopilotStudioWebChat.createConnection(client, {
  showTyping: true,
});

window.WebChat.renderWebChat({
  directLine,
}, document.getElementById("webchat")!);

Best Practices

  1. Use AgentApplication for routing and keep handlers focused on one responsibility.
  2. Prefer streamingResponse for long-running completions and call endStream in finally blocks.
  3. Keep secrets out of source code; load tokens from environment variables or secure stores.
  4. Reuse CopilotStudioClient instances and cache tokens in your token provider.
  5. Validate invoke payloads before logging or persisting feedback.

Reference Files

FileContents
references/acceptance-criteria.mdImport paths, hosting pipeline, streaming, and Copilot Studio patterns

Reference Links

ResourceURL
Microsoft 365 Agents SDKhttps://learn.microsoft.com/en-us/microsoft-365/agents-sdk/
JavaScript SDK overviewhttps://learn.microsoft.com/en-us/javascript/api/overview/agents-overview?view=agents-sdk-js-latest
@microsoft/agents-hosting-expresshttps://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-hosting-express?view=agents-sdk-js-latest
@microsoft/agents-copilotstudio-clienthttps://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-copilotstudio-client?view=agents-sdk-js-latest
Integrate with Copilot Studiohttps://learn.microsoft.com/en-us/microsoft-365/agents-sdk/integrate-with-mcs
GitHub sampleshttps://github.com/microsoft/Agents/tree/main/samples/nodejs

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

When not to use it

  • When using unverified API signatures

Prerequisites

Node.jsAzure OpenAI resource

Limitations

  • Requires valid environment variables for authentication
  • Streaming responses must be explicitly managed

How it compares

It provides a specialized SDK for Microsoft 365 and Copilot Studio integration rather than generic chatbot development.

Compared to similar skills

m365-agents-ts side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
m365-agents-ts (this skill)05moReviewIntermediate
mcp-server-patterns03moReviewIntermediate
mcp-builder1363moReviewAdvanced
telegram-mini-app626moReviewAdvanced

Try saying

Example prompts that trigger this skill in your AI assistant.

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