How to integrate Todoist MCP with LangChain

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Introduction

This guide walks you through connecting Todoist to LangChain 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 through natural language commands.

This guide will help you understand how to give your LangChain 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.

Also integrate Todoist with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Todoist project to Composio
  • Create a Tool Router MCP session for Todoist
  • Initialize an MCP client and retrieve Todoist tools
  • Build a LangChain agent that can interact with Todoist
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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.
Archive Project (API v1)Tool to archive a project using Todoist API v1.
Bulk Create TasksCreate many tasks in one request using Todoist's Sync batching.
Close Task (API v1)Tool to close (complete) a task in Todoist using API v1.
Create Comment (API v1)Tool to create a new comment on a project or task using Todoist API v1.
Create Label (API v1)Tool to create a new personal label using API v1.
Create Project (API v1)Tool to create a new project in Todoist using the unified API v1.
Create Section (API v1)Tool to create a new section within a project using API v1.
Create taskCreate a new task in Todoist using the unified API v1.
Delete CommentTool to delete a specific comment from Todoist by its ID.
Delete Label (V1)Tool to delete a personal label using API v1.
Delete Project (API v1)Tool to delete a project and all of its sections and tasks using Todoist API v1.
Delete Section (v1)Tool to delete a section and all tasks within it.
Delete TaskTool to delete a specific task from Todoist.
Delete UploadTool to delete an uploaded file from Todoist.
Export Template As FileTool to export a Todoist project as a CSV template file.
Export Template As URLTool to export a Todoist project as a shareable template URL.
Filter TasksTool to get all tasks matching the filter.
Get All CommentsThis tool retrieves all comments associated with a specific task or project in Todoist.
Get all projectsGet all projects from a user's Todoist account.
Get All TasksFetches all INCOMPLETE tasks from Todoist and returns their details.
Get BackupsTool to list all available backup archives for the user.
Get Comment (V1)Tool to retrieve a single comment by ID using the v1 API.
Get Completed Tasks By Completion DateTool to retrieve completed tasks within a specified completion date window.
Get ID MappingsTool to translate IDs between Todoist API v1 and v2.
Get Personal LabelTool to retrieve a personal label by its ID.
Get Productivity StatsTool to retrieve comprehensive productivity statistics for the authenticated user.
Get Project (API v1)Tool to retrieve a specific project by its ID using Todoist API v1.
Get Full Project DataTool to retrieve full project data including all sections, tasks, and collaborators.
Get Project PermissionsTool to retrieve all available roles and their associated actions in Todoist projects.
Get Section (v1 API)Tool to retrieve a specific section by its ID using Todoist v1 API.
Get Special BackupsTool to list special backup archives for the authenticated user's projects.
Get Task (API v1)Tool to retrieve a single active (non-completed) task by ID using API v1.
Get UserTool to retrieve information about the currently authenticated user.
Get Workspace Plan DetailsTool to retrieve details about a workspace's current plan and usage.
Import Template Into Project By IDTool to import a template from Todoist's template gallery into an existing project.
Import Template Into Project From FileTool to import a CSV template into an existing Todoist project from a file.
Invite Project CollaboratorTool to invite a collaborator to a Todoist project by email.
List ActivitiesTool to get activity logs from Todoist.
List All Workspace InvitationsTool to return a list containing details of all pending invitations to a workspace.
List Archived ProjectsTool to get all archived projects from Todoist.
List Archived SectionsTool to retrieve all archived sections for a specific project in Todoist.
List Archived Workspace ProjectsTool to list all archived projects in a workspace.
List Completed TasksTool to retrieve all completed tasks with optional project filtering.
List Completed Tasks By Due DateTool to retrieve completed tasks within a specified due date range (up to 6 weeks).
List FiltersTool to list all filters for the authenticated user.
List Joinable WorkspacesTool to get workspaces the user can join.
List LabelsTool to get all user labels with pagination support.
List Pending Workspace InvitationsTool to list pending invitation emails in a workspace.
List Project CollaboratorsTool to get all collaborators for a given project with cursor-based pagination.
List SectionsTool to get all active sections for the user, with optional filtering by project.
List Shared LabelsTool to retrieve shared label names from active tasks with pagination support.
List Workspace Active ProjectsTool to list all active workspace projects.
List Workspace Archived ProjectsTool to get archived projects in a workspace.
List Workspace InvitationsTool to list user emails with pending invitations to a workspace.
List Workspace UsersTool to list users in workspace(s).
Move TaskTool to move a task to another project, section, or parent task while preserving task identity and metadata.
Move Task (REST API)Tool to move a task to another project, section, or parent task using the REST API.
Quick Add TaskTool to add tasks using natural language parsing similar to the official Todoist clients.
Remove Shared Label (API v1)Tool to remove a shared label from all active tasks using API v1.
Rename Shared Labels (API v1)Tool to rename a shared label across all active tasks using API v1.
Reopen Task (API v1)Tool to reopen a completed task in Todoist using API v1.
Reorder TasksReorder tasks deterministically by updating child_order in bulk via the Sync API item_reorder command.
Search LabelsTool to search user labels by name with case-insensitive matching.
Search ProjectsSearch active user projects by name with support for wildcards and pagination.
Search SectionsTool to search active sections by name, optionally filtered by project.
Todoist SyncTool to sync data with Todoist server, supporting both read and write operations.
Unarchive Project (API v1)Tool to unarchive a previously archived Todoist project using API v1.
Update Comment (v1)Tool to update a comment by ID and return its content via v1 API.
Update Label (API v1)Tool to update an existing label using API v1.
Update Notification SettingTool to update notification settings for the current user.
Update Project (API v1)Tool to update a project's properties using Todoist API v1.
Update Section (v1)Tool to update an existing section by its ID using Todoist v1 API.
Update TaskTool to update an existing task's properties.
Update Workspace LogoTool to upload an image as the workspace logo or delete the existing logo.
Upload FileTool to upload a file to Todoist.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Todoist functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Todoist tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Todoist
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['todoist']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Todoist tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Todoist tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "todoist-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Todoist MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Todoist tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Todoist related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

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

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['todoist']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "todoist-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Todoist related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Todoist through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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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 LangChain?

Yes, you can. LangChain 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.

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