m365-agents-ts
Allows creating AI agents for Microsoft 365 using TypeScript. It helps develop assistants that integrate with the Microsoft environment.
What it does
This is a toolkit for building smart virtual assistants (agents) that work within the Microsoft ecosystem, such as Teams and Copilot Studio. It allows developers to create advanced conversational experiences.
When to use it
- ✓When you want to build a custom chatbot for Microsoft Teams.
- ✓When developing a virtual assistant that integrates with Copilot Studio.
- ✓To build applications that respond to messages dynamically and in real-time.
Example of what to ask your AI
“How can I set up an agent to respond to messages in Teams?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It works by connecting to Microsoft services and using code to define how the agent should respond to different types of messages or events. The code manages the communication and conversation flow.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill m365-agents-tsOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/m365-agents-ts/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Supporting material availability
This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files:
<support-root>/references/acceptance-criteria.md
Ask for the original supporting material or an existing installation before using a step that depends on these paths; this catalog does not identify a verified download source for them. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable.
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)
…
FAQ
What are 'agents' in this context?
Agents are computer programs that can understand and respond to commands or questions, acting as virtual assistants.
Do I need to know how to code to use this?
Yes, this toolkit is for developers who know how to code, as it involves writing code to set up the agent.
What is 'streaming responses'?
It's a way for the agent to send its response in small pieces as it's generated, rather than waiting for the whole response. This makes the interaction feel faster and smoother.
Details
Original description by the author
Microsoft 365 Agents SDK for TypeScript/Node.js.
Popularity
- GitHub stars
- 48k
- Ranking position
- #3509
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
More skills from this repository
00-andruia-consultant
Helps your agent start or improve AI projects. It analyzes code, suggests tools, and creates action plans in Spanish.
sickn33/agentic-awesome-skills
007
Lets your agent perform security audits and threat modeling. It's useful for protecting projects against attacks and vulnerabilities.
sickn33/agentic-awesome-skills
10-andruia-skill-smith
Helps your agent create or improve AI tools. It defines how tools work, writes documentation, and validates the structure.
sickn33/agentic-awesome-skills
20-andruia-niche-intelligence
Lets your agent create a summary about a specific industry. It's useful for understanding the context, rules, usage patterns, and risks of a project, using reliable sources.
sickn33/agentic-awesome-skills
Similar skills
agent-architecture-audit
Makes your agent check if everything is working correctly. It finds and fixes problems in AI systems, ensuring they perform as expected.
affaan-m/ECC
agent-eval
Helps your agent compare different AI coding tools. It measures which one is faster, cheaper, and more reliable for specific tasks.
affaan-m/ECC
agent-harness-construction
Makes your agent better understand how to perform tasks. It optimizes the tools and instructions the agent uses to increase its chances of success.
affaan-m/ECC