How to integrate Todoist MCP with Mastra AI

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Introduction

This guide walks you through connecting Todoist to Mastra AI using the Composio tool router. By the end, you'll have a working Todoist agent that can add a high-priority task for today, create a new project called 'team offsite', close all completed tasks from this week, add a comment to my 'marketing plan' task through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Todoist account through Composio's Todoist MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Set up your environment so Mastra, OpenAI, and Composio work together
  • Create a Tool Router session in Composio that exposes Todoist tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Todoist tool definitions and attach them as a toolset
  • Build a Mastra agent that can reason, call tools, and return structured results
  • Run an interactive CLI where you can chat with your Todoist agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

  • MCP Client: Built-in support for Model Context Protocol servers
  • Toolsets: Organize tools into logical groups
  • Step Callbacks: Monitor and debug agent execution
  • OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

What is the Todoist MCP server, and what's possible with it?

The Todoist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Todoist account. It provides structured and secure access to your tasks, projects, and labels, so your agent can create tasks, manage projects, add comments, organize sections, and update your to-do lists on your behalf.

  • Task creation and scheduling: Instantly ask your agent to add new tasks with specific details, deadlines, priorities, or even as subtasks within projects or sections.
  • Project and workspace management: Let your agent create, organize, or delete projects and workspaces to keep your productivity system tidy and up-to-date.
  • Section and label organization: Direct your agent to create, delete, or update sections and labels, helping you structure your tasks and filter lists for better focus.
  • Task completion and commenting: Have your agent mark tasks as complete or add helpful comments and notes to specific tasks or projects for seamless collaboration.
  • Streamlined cleanup and maintenance: Empower your agent to remove unused projects, labels, or sections, ensuring your Todoist stays clutter-free and organized.

Supported Tools & Triggers

Tools
Triggers
Add WorkspaceTool to create a new workspace in todoist.
Close TaskThis tool marks an existing task as completed in todoist.
Create CommentTool to create a new comment in todoist.
Create LabelCreates a new label.
Create ProjectCreates a new project in todoist.
Create SectionTool to create a new section within a specific project.
Create taskCreate a new task in todoist.
Delete LabelTool to delete a specific label.
Delete ProjectTool to delete a specific todoist project.
Delete SectionTool to delete a specific section.
Delete taskDelete a task from todoist.
Get All CommentsThis tool retrieves all comments associated with a specific task or project in todoist.
Get all labelsGet all personal labels from todoist.
Get all projectsGet all projects from a user's todoist account.
Get All SectionsTool to retrieve all sections for a specific project in todoist.
Get All TasksFetches all tasks from todoist and returns their details.
Get BackupsTool to list all available backup archives for the user.
Get CommentTool to retrieve details of a specific comment by its comment id.
Get LabelTool to retrieve a specific label by its id.
Get ProjectTool to retrieve a specific project by its id.
Get SectionTool to retrieve a specific section by its id.
Get Special BackupsTool to list special backup archives for the user.
Get TaskTool to retrieve a specific task by its id.
List Archived Workspace ProjectsTool to list all archived projects in a workspace.
List FiltersTool to list all filters for the authenticated user.
List Pending Workspace InvitationsTool to list pending invitation emails in a workspace.
Reopen TaskThis tool reopens a previously completed task.
Update CommentTool to update a specific comment's content.
Update ProjectTool to update a specific project's attributes such as name, color, indent, and order.
Update SectionTool to update a specific section's attributes such as name and order.
Update TaskTool to update an existing task's properties.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key.
  • You need credits or a connected billing setup to use the models.
  • Store the key somewhere safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Go to Settings and copy your API key.
  • This key lets your Mastra agent talk to Composio and reach Todoist through MCP.

Install dependencies

bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

  • @composio/core is the Composio SDK for creating MCP sessions
  • @mastra/core provides the Agent class
  • @mastra/mcp is Mastra's MCP client
  • @ai-sdk/openai is the model wrapper for OpenAI
  • dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio
  • COMPOSIO_USER_ID tells Composio which user this session belongs to
  • OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey as string,
});
What's happening:
  • dotenv/config auto loads your .env so process.env.* is available
  • openai gives you a Mastra compatible model wrapper
  • Agent is the Mastra agent that will call tools and produce answers
  • MCPClient connects Mastra to your Composio MCP server
  • Composio is used to create a Tool Router session

Create a Tool Router session for Todoist

typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["todoist"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Todoist MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "todoist" for Todoist access
  • session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
What's happening:
  • MCPClient takes an id for this client and a list of MCP servers
  • The headers property includes the x-api-key for authentication
  • getTools fetches the tool definitions exposed by the Todoist toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "todoist-mastra-agent",
    instructions: "You are an AI agent with Todoist tools via Composio.",
    model: "openai/gpt-5",
  });
What's happening:
  • Agent is the core Mastra agent
  • name is just an identifier for logging and debugging
  • instructions guide the agent to use tools instead of only answering in natural language
  • model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\n");

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

  if (!trimmedInput) {
    rl.prompt();
    return;
  }

  messages.push({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        todoist: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main().catch((err) => {
  console.error("Fatal error:", err);
  process.exit(1);
});
What's happening:
  • messages keeps the full conversation history in Mastra's expected format
  • agent.generate runs the agent with conversation history and Todoist toolsets
  • maxSteps limits how many tool calls the agent can take in a single run
  • onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Todoist and Mastra AI:

typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({ apiKey: composioAPIKey as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["todoist"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      todoist: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "todoist-mastra-agent",
    instructions: "You are an AI agent with Todoist tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { todoist: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Todoist through Composio's Tool Router. You can extend this further by:
  • Adding other toolkits like Gmail, Slack, or GitHub
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows

How to build Todoist MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Todoist MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Todoist MCP with Claude Agent SDK

Google ADK

Google ADK

Use Todoist MCP with Google ADK

LangChain

LangChain

Use Todoist MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Todoist MCP with Vercel AI SDK

LlamaIndex

LlamaIndex

Use Todoist MCP with LlamaIndex

CrewAI

CrewAI

Use Todoist MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Todoist MCP?

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

Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI 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 Todoist tools.

Can I manage the permissions and scopes for Todoist while using Tool Router?

Yes, absolutely. You can configure which Todoist 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 Todoist data and credentials are handled as safely as possible.

Used by agents from

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HubSpot
Agent.ai
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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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