# How to integrate Microsoft teams MCP with LlamaIndex

```json
{
  "title": "How to integrate Microsoft teams MCP with LlamaIndex",
  "toolkit": "Microsoft teams",
  "toolkit_slug": "microsoft_teams",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/microsoft_teams/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/microsoft_teams/framework/llama-index.md",
  "updated_at": "2026-05-06T08:20:13.617Z"
}
```

## Introduction

This guide walks you through connecting Microsoft teams to LlamaIndex using the Composio tool router. By the end, you'll have a working Microsoft teams agent that can add new member to project team, schedule an online meeting for sales, list all chats i’m part of through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Microsoft teams account through Composio's Microsoft teams MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Microsoft teams with

- [ChatGPT](https://composio.dev/toolkits/microsoft_teams/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/microsoft_teams/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/microsoft_teams/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/microsoft_teams/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/microsoft_teams/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/microsoft_teams/framework/codex)
- [Cursor](https://composio.dev/toolkits/microsoft_teams/framework/cursor)
- [VS Code](https://composio.dev/toolkits/microsoft_teams/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/microsoft_teams/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/microsoft_teams/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/microsoft_teams/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/microsoft_teams/framework/cli)
- [Google ADK](https://composio.dev/toolkits/microsoft_teams/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/microsoft_teams/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/microsoft_teams/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/microsoft_teams/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/microsoft_teams/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Microsoft teams
- Connect LlamaIndex to the Microsoft teams MCP server
- Build a Microsoft teams-powered agent using LlamaIndex
- Interact with Microsoft teams through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## What is the Microsoft teams MCP server, and what's possible with it?

The Microsoft Teams MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Microsoft Teams account. It provides structured and secure access to your Teams workspace, so your agent can perform actions like managing chats, sending messages, creating meetings, and organizing teams on your behalf.
- Automated chat and message management: Let your agent retrieve, read, and summarize messages from any Teams chat, or fetch all chats you’re part of for quick updates.
- Team and channel organization: Easily create new teams, add members, get channel details, or archive and delete teams to keep your workspace organized.
- Scheduling online meetings: Have your agent schedule standalone Teams meetings instantly, making it simple to coordinate with colleagues or clients without manual setup.
- Granular access to team and chat details: Fetch full information about specific teams, channels, or even individual messages with precision, enabling rich contextual workflows.
- Seamless membership and collaboration management: Add or update members in teams with a prompt, ensuring the right people always have access to the conversations and resources they need.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MICROSOFT_TEAMS_ADD_MEMBER_TO_TEAM` | Add member to team | Tool to add a user to a microsoft teams team. use when granting or updating membership for a user. |
| `MICROSOFT_TEAMS_ARCHIVE_TEAM` | Archive Teams team | Tool to archive a microsoft teams team. use after confirming the team id; returns 202 if accepted. |
| `MICROSOFT_TEAMS_CHATS_GET_ALL_CHATS` | Get all chats | Retrieves all microsoft teams chats a specified user is part of, supporting filtering, property selection, and pagination. |
| `MICROSOFT_TEAMS_CHATS_GET_ALL_MESSAGES` | Get all chat messages | Retrieves all messages from a specified microsoft teams chat using the microsoft graph api, automatically handling pagination; ensure `chat id` is valid and odata expressions in `filter` or `select` are correct. |
| `MICROSOFT_TEAMS_CREATE_MEETING` | Create online meeting | Use to schedule a new standalone microsoft teams online meeting, i.e., one not linked to any calendar event. |
| `MICROSOFT_TEAMS_CREATE_TEAM` | Create Team | Tool to create a new microsoft teams team. use when you need to provision a team with optional template, channels, and members. |
| `MICROSOFT_TEAMS_DELETE_TEAM` | Delete Teams team | Tool to delete a microsoft teams team. use after confirming the target team id. |
| `MICROSOFT_TEAMS_GET_CHANNEL` | Get team channel | Tool to get a specific channel in a team. use after obtaining valid team and channel ids to fetch channel details. |
| `MICROSOFT_TEAMS_GET_CHAT_MESSAGE` | Get chat message | Tool to get a specific chat message. use after confirming chat id and message id. |
| `MICROSOFT_TEAMS_GET_TEAM` | Get Team | Tool to get a specific team. use when full details of one team by id are needed. |
| `MICROSOFT_TEAMS_LIST_MESSAGE_REPLIES` | List message replies | Tool to list replies to a channel message. use after obtaining team, channel, and message ids. |
| `MICROSOFT_TEAMS_LIST_TEAM_MEMBERS` | List team members | Tool to list members of a microsoft teams team. use when you need to retrieve the members of a specific team, for auditing or notifications. |
| `MICROSOFT_TEAMS_LIST_TEAMS_TEMPLATES` | List Teams templates | Tool to list available microsoft teams templates. use when retrieving templates for team creation or customization workflows. |
| `MICROSOFT_TEAMS_LIST_USERS` | List users | Tool to list all users in the organization. use when you need to retrieve directory users with filtering, pagination, and field selection. |
| `MICROSOFT_TEAMS_TEAMS_CREATE_CHANNEL` | Create a channel | Creates a new 'standard', 'private', or 'shared' channel within a specified microsoft teams team. |
| `MICROSOFT_TEAMS_TEAMS_CREATE_CHAT` | Create Chat | Creates a new chat; if a 'oneonone' chat with the specified members already exists, its details are returned, while 'group' chats are always newly created. |
| `MICROSOFT_TEAMS_TEAMS_GET_MESSAGE` | Get Teams message | Retrieves a specific message from a microsoft teams channel using its team, channel, and message ids. |
| `MICROSOFT_TEAMS_TEAMS_LIST` | List Teams | Retrieves microsoft teams accessible by the authenticated user, allowing filtering, property selection, and pagination. |
| `MICROSOFT_TEAMS_TEAMS_LIST_CHANNELS` | List team channels | Retrieves channels for a specified microsoft teams team id (must be valid and for an existing team), with options to include shared channels, filter results, and select properties. |
| `MICROSOFT_TEAMS_TEAMS_LIST_CHAT_MESSAGES` | List chat messages | Retrieves messages (newest first) from an existing and accessible microsoft teams one-on-one chat, group chat, or channel thread, specified by `chat id`. |
| `MICROSOFT_TEAMS_TEAMS_LIST_PEOPLE` | List People | Retrieves a list of people relevant to a specified user from microsoft graph, noting the `search` parameter is only effective if `user id` is 'me'. |
| `MICROSOFT_TEAMS_TEAMS_POST_CHANNEL_MESSAGE` | Post message to Teams channel | Posts a new text or html message to a specified channel in a microsoft teams team. |
| `MICROSOFT_TEAMS_TEAMS_POST_CHAT_MESSAGE` | Send message to Teams chat | Sends a non-empty message (text or html) to a specified, existing microsoft teams chat; content must be valid html if `content type` is 'html'. |
| `MICROSOFT_TEAMS_TEAMS_POST_MESSAGE_REPLY` | Reply to Teams channel message | Sends a reply to an existing message, identified by `message id`, within a specific `channel id` of a given `team id` in microsoft teams. |
| `MICROSOFT_TEAMS_UNARCHIVE_TEAM` | Unarchive Teams team | Tool to unarchive a microsoft teams team. use when you need to restore an archived team to active state. |
| `MICROSOFT_TEAMS_UPDATE_CHANNEL_MESSAGE` | Update Teams channel message | Tool to update a message in a channel. use when you need to modify an existing channel message after confirming channel and message ids. |
| `MICROSOFT_TEAMS_UPDATE_CHAT_MESSAGE` | Update Teams chat message | Tool to update a specific message in a chat. use when you need to correct or modify a sent chat message. |
| `MICROSOFT_TEAMS_UPDATE_TEAM` | Update Team | Tool to update the properties of a team. use when you need to modify team settings such as member, messaging, or fun settings. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Microsoft teams MCP server is an implementation of the Model Context Protocol that connects your AI agent to Microsoft teams. It provides structured and secure access so your agent can perform Microsoft teams operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Microsoft teams account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Microsoft teams

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Microsoft teams access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, microsoft teams)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Microsoft teams tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["microsoft_teams"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Microsoft teams actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Microsoft teams actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["microsoft_teams"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Microsoft teams actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Microsoft teams
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Microsoft teams, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["microsoft_teams"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Microsoft teams actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Microsoft teams actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["microsoft_teams"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Microsoft teams actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Microsoft teams to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Microsoft teams tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Microsoft teams MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/microsoft_teams/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/microsoft_teams/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/microsoft_teams/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/microsoft_teams/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/microsoft_teams/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/microsoft_teams/framework/codex)
- [Cursor](https://composio.dev/toolkits/microsoft_teams/framework/cursor)
- [VS Code](https://composio.dev/toolkits/microsoft_teams/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/microsoft_teams/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/microsoft_teams/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/microsoft_teams/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/microsoft_teams/framework/cli)
- [Google ADK](https://composio.dev/toolkits/microsoft_teams/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/microsoft_teams/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/microsoft_teams/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/microsoft_teams/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/microsoft_teams/framework/crew-ai)

## Related Toolkits

- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.
- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere.
- [Heartbeat](https://composio.dev/toolkits/heartbeat) - Heartbeat is a plug-and-play platform for building and managing online communities. It helps you organize users, channels, events, and discussions in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Microsoft teams MCP?

With a standalone Microsoft teams MCP server, the agents and LLMs can only access a fixed set of Microsoft teams tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Microsoft teams and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Microsoft teams tools.

### Can I manage the permissions and scopes for Microsoft teams while using Tool Router?

Yes, absolutely. You can configure which Microsoft teams scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Microsoft teams data and credentials are handled as safely as possible.

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)