# How to integrate Microsoft To Do MCP with LlamaIndex

```json
{
  "title": "How to integrate Microsoft To Do MCP with LlamaIndex",
  "toolkit": "Microsoft To Do",
  "toolkit_slug": "microsoft_todo",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/microsoft_todo/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/microsoft_todo/framework/llama-index.md",
  "updated_at": "2026-07-28T11:13:30.103Z"
}
```

## Introduction

This guide walks you through connecting Microsoft To Do to LlamaIndex using the Composio tool router. By the end, you'll have a working Microsoft To Do agent that can create task for tomorrow's expense report, list overdue tasks from all lists, add reminder to project checklist item through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Microsoft To Do account through Composio's Microsoft To Do MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Microsoft To Do with

- [OpenAI Agents SDK](https://composio.dev/toolkits/microsoft_todo/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/microsoft_todo/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/microsoft_todo/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/microsoft_todo/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/microsoft_todo/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/microsoft_todo/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/microsoft_todo/framework/hermes-agent)
- [Google ADK](https://composio.dev/toolkits/microsoft_todo/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/microsoft_todo/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/microsoft_todo/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/microsoft_todo/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/microsoft_todo/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/microsoft_todo/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/microsoft_todo/framework/autogen)

## 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 To Do
- Connect LlamaIndex to the Microsoft To Do MCP server
- Build a Microsoft To Do-powered agent using LlamaIndex
- Interact with Microsoft To Do 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 To Do MCP server, and what's possible with it?

The Microsoft To Do 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 To Do account. It provides structured and secure access so your agent can perform Microsoft To Do operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MICROSOFT_TODO_COMPLETE_TASK` | Complete Task | Mark a Microsoft To Do task as completed. Convenience wrapper that always PATCHes status='completed'; the server auto-sets completedDateTime. Use Update Task to reopen a task (status='notStarted') or to change other fields. |
| `MICROSOFT_TODO_CREATE_CHECKLIST_ITEM` | Create Checklist Item | Add a checklist item (subtask) to a Microsoft To Do task. Only display_name is required; the created item is returned with a GUID id, displayName, isChecked, and createdDateTime. |
| `MICROSOFT_TODO_CREATE_TASK` | Create Task | Create a task in a Microsoft To Do task list. Only title is required. Dates are passed as flat ISO-8601 strings plus a shared timezone; the tool builds the Graph dateTimeTimeZone objects. Notes are passed as body_content (+ body_content_type). NOTE: To Do treats due dates as whole days — the time component of due_date_time is normalized to midnight on save. |
| `MICROSOFT_TODO_CREATE_TASK_LIST` | Create Task List | Create a new Microsoft To Do task list. |
| `MICROSOFT_TODO_DELETE_CHECKLIST_ITEM` | Delete Checklist Item | Delete a checklist item (subtask) from a Microsoft To Do task. This permanently removes the checklist item (this cannot be undone). |
| `MICROSOFT_TODO_DELETE_TASK` | Delete Task | Delete a task from a Microsoft To Do task list. WARNING: this also permanently removes the task's checklist items and linked resources. |
| `MICROSOFT_TODO_DELETE_TASK_ATTACHMENT` | Delete Task Attachment | Permanently delete a file attachment from a Microsoft To Do task. This cannot be undone. |
| `MICROSOFT_TODO_DELETE_TASK_LIST` | Delete Task List | Delete a Microsoft To Do task list. WARNING: this cascades — all tasks in the list and their checklist items are permanently deleted. |
| `MICROSOFT_TODO_DOWNLOAD_TASK_ATTACHMENT` | Download Task Attachment | Download one file attached to a Microsoft To Do task. The file is offloaded to storage and returned as a downloadable reference rather than inline base64. |
| `MICROSOFT_TODO_GET_CHECKLIST_ITEM` | Get Checklist Item | Get a single Microsoft To Do checklist item (subtask) by its id, within a task in a task list. |
| `MICROSOFT_TODO_GET_CURRENT_USER` | Get Current User | Return the profile of the Microsoft account connected to this toolkit (whoami / connection verification). Useful to confirm which mailbox the To Do tasks belong to before other operations. |
| `MICROSOFT_TODO_GET_TASK` | Get Task | Get a single Microsoft To Do task by its id, within a task list. Set include_checklist_items=true to expand its checklist items inline. |
| `MICROSOFT_TODO_GET_TASK_ATTACHMENT` | Get Task Attachment | Get metadata for one file attached to a Microsoft To Do task. Use Download Task Attachment to retrieve the file contents. |
| `MICROSOFT_TODO_GET_TASK_LIST` | Get Task List | Get a single Microsoft To Do task list by its id. |
| `MICROSOFT_TODO_LIST_CHECKLIST_ITEMS` | List Checklist Items | List the checklist items (subtasks) of a To Do task. Auto-paginates so all subtasks are returned at once as {items: [...]}. |
| `MICROSOFT_TODO_LIST_TASK_ATTACHMENTS` | List Task Attachments | List the files attached to a Microsoft To Do task. Returns attachment metadata without file contents, one page at a time, plus a next_cursor. |
| `MICROSOFT_TODO_LIST_TASK_LISTS` | List Task Lists | List the To Do task lists owned by the connected user. The built-in default list has wellknown_list_name='defaultList'; user-created lists have wellknown_list_name='none'. Always returns at least the default list. Select the default list by id or wellknown_list_name, never by the localized display_name. |
| `MICROSOFT_TODO_LIST_TASKS` | List Tasks | List the tasks in a To Do task list. Checklist items (subtasks) are NOT returned by default; set include_checklist_items=true to expand them inline. Returns one page of tasks plus a next_cursor for the next page. |
| `MICROSOFT_TODO_UPDATE_CHECKLIST_ITEM` | Update Checklist Item | Update a checklist item (subtask) of a Microsoft To Do task: rename it (display_name) and/or check/uncheck it (is_checked). Partial update: only the fields you pass are changed; at least one is required. Setting is_checked=true marks the subtask done. |
| `MICROSOFT_TODO_UPDATE_TASK` | Update Task | Update fields of an existing Microsoft To Do task (title, notes, importance, status, due/start/reminder dates, categories). Partial update: only the fields you pass are changed; unset fields are left untouched. To mark a task done set status='completed' (or use the dedicated Complete Task tool). |
| `MICROSOFT_TODO_UPDATE_TASK_LIST` | Update Task List | Rename a Microsoft To Do task list (updates its displayName). |
| `MICROSOFT_TODO_UPLOAD_TASK_ATTACHMENT` | Upload Task Attachment | Attach a file up to 25 MB to a Microsoft To Do task. The tool automatically uses a single request for files under 3 MB and a chunked upload session for larger files. |

## Supported Triggers

None listed.

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

The Microsoft To Do MCP server is an implementation of the Model Context Protocol that connects your AI agent to Microsoft To Do. It provides structured and secure access so your agent can perform Microsoft To Do 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 To Do account and project
- Basic familiarity with async Python/Typescript

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

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 To Do 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 to do)
- 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 To Do 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_todo"],
    )

    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 To Do actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Microsoft To Do 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_todo"],
    },
  );

  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 To Do 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 To Do
```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 To Do, 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_todo"],
    )

    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 To Do actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Microsoft To Do 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_todo"],
    },
  );

  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 To Do 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 To Do to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Microsoft To Do 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 To Do MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/microsoft_todo/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/microsoft_todo/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/microsoft_todo/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/microsoft_todo/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/microsoft_todo/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/microsoft_todo/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/microsoft_todo/framework/hermes-agent)
- [Google ADK](https://composio.dev/toolkits/microsoft_todo/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/microsoft_todo/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/microsoft_todo/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/microsoft_todo/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/microsoft_todo/framework/crew-ai)
- [Pydantic AI](https://composio.dev/toolkits/microsoft_todo/framework/pydantic-ai)
- [AutoGen](https://composio.dev/toolkits/microsoft_todo/framework/autogen)

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [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.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page.
- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights.
- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.

## Frequently Asked Questions

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

With a standalone Microsoft To Do MCP server, the agents and LLMs can only access a fixed set of Microsoft To Do tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Microsoft To Do 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 To Do tools.

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

Yes, absolutely. You can configure which Microsoft To Do 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 To Do 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)