m365-agents-ts
microsoft/skills
Microsoft 365 エージェント SDK を使用して、Express ホスティング、AgentApplication ルーティング、ストリーミングレスポンス、および Copilot Studio クライアント統合により、Microsoft 365、Teams、Copilot Studio 用のエンタープライズエージェントを構築します。
...すべて拡張しますMicrosoft 365 エージェント SDK (TypeScript)
Microsoft 365 エージェント SDK を使用して、Express ホスティング、AgentApplication ルーティング、ストリーミングレスポンス、および Copilot Studio クライアント統合により、Microsoft 365、Teams、Copilot Studio 用のエンタープライズエージェントを構築します。
実装前の準備
microsoft-docs MCPを使用して、AgentApplication、startServer、CopilotStudioClient の最新の API シグネチャを確認します。- サンプルやテンプレートを接続する前に、npm 上のパッケージバージョンを確認します。
インストール
npm install @microsoft/agents-hosting @microsoft/agents-hosting-express @microsoft/agents-activity
npm install @microsoft/agents-copilotstudio-client
環境変数
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></copilot-jwt></copilot-app-client-id></schema-name></environment-id></client-secret></client-id></tenant-id></azure-openai-key></azure-openai-resource>
コアワークフロー: Express ホスト型 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);
</turnstate>
Azure OpenAI によるストリーミングレスポンス
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);
</turnstate>
Invoke アクティビティの処理
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.");
});
</turnstate>
Copilot Studio クライアント(エンジンへの直接接続)
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);
</string>
Copilot Studio WebChat 統合
import { CopilotStudioWebChat } from "@microsoft/agents-copilotstudio-client";
const directLine = CopilotStudioWebChat.createConnection(client, {
showTyping: true,
});
window.WebChat.renderWebChat(
{
directLine,
},
document.getElementById("webchat")!,
);
ベストプラクティス
- ルーティングには AgentApplication を使用し、ハンドラーは単一の責任に焦点を当ててください。
- 長時間実行される完了処理には streamingResponse を優先し、finally ブロックで endStream を呼び出してください。
- 秘密鍵をソースコードに含めないでください。トークンは環境変数または安全なストアから読み込んでください。
- CopilotStudioClient インスタンスを再利用し、トークンプロバイダーでトークンをキャッシュしてください。
- フィードバックをログに記録または永続化する前に、invoke ペイロードを検証してください。
参照リンク
| リソース | URL |
|---|---|
| Microsoft 365 エージェント SDK | https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/ |
| JavaScript SDK 概要 | https://learn.microsoft.com/en-us/javascript/api/overview/agents-overview?view=agents-sdk-js-latest |
| @microsoft/agents-hosting-express | https://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-hosting-express?view=agents-sdk-js-latest |
| @microsoft/agents-copilotstudio-client | https://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-copilotstudio-client?view=agents-sdk-js-latest |
| Copilot Studio への統合 | https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/integrate-with-mcs |
| GitHub サンプル | https://github.com/microsoft/Agents/tree/main/samples/nodejs |
---
name: m365-agents-ts
description: 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.
license: MIT
---
# 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
```bash
npm install @microsoft/agents-hosting @microsoft/agents-hosting-express @microsoft/agents-activity
npm install @microsoft/agents-copilotstudio-client
```
## Environment Variables
```bash
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
```typescript
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
```typescript
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
```typescript
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)
```typescript
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
```typescript
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 Links
| Resource | URL |
| -------------------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| Microsoft 365 Agents SDK | https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/ |
| JavaScript SDK overview | https://learn.microsoft.com/en-us/javascript/api/overview/agents-overview?view=agents-sdk-js-latest |
| @microsoft/agents-hosting-express | https://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-hosting-express?view=agents-sdk-js-latest |
| @microsoft/agents-copilotstudio-client | https://learn.microsoft.com/en-us/javascript/api/%40microsoft/agents-copilotstudio-client?view=agents-sdk-js-latest |
| Integrate with Copilot Studio | https://learn.microsoft.com/en-us/microsoft-365/agents-sdk/integrate-with-mcs |
| GitHub samples | https://github.com/microsoft/Agents/tree/main/samples/nodejs |
すべてのファイル
0件のファイルm365-agents-tsをインストール
スキルファイルをダウンロードして .claude/skills/ ディレクトリに展開してください。
ZIPをダウンロードリポジトリをクローンし、スキルファイルをプロジェクトにコピーしてください。
git clone https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-typescript/skills/m365-agents-ts # Copy SKILL.md to your .claude/skills/ directory
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