Where do I get my Todoist API Token?

You can locate your personal API Token securely via the web application by clicking your profile avatar, going to **Settings**, and selecting the **Integrations** tab. Your token will be visible at the bottom or in a dedicated Developer section. Alternatively, navigate directly to `https://todoist.com/prefs/integrations`.

Can the agent delete projects or workspaces?

No. The integration exclusively lists resources (projects, items, labels) and supports only basic item modifications: creating tasks and marking tasks as completed. Destructive actions on structural settings are not supported.

Can the agent organize my tasks using sub-projects or sections?

Yes. The Todoist integration allows the agent to retrieve project IDs and navigate into their specific sections. When creating a new task, you can explicitly ask the agent to place it within a specific section to keep your work neatly organized.

Todoist MCP Server for LangChain 7 tools — connect in under 2 minutes

Name: Todoist
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 7 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Todoist through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "todoist": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Todoist, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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About Todoist MCP Server

Connect your Todoist account to any AI agent and bring your daily productivity directly into your chat. View your active tasks, manage projects, and quickly add new items to your workflow entirely through conversational commands without ever needing to open the app.

LangChain's ecosystem of 500+ components combines seamlessly with Todoist through native MCP adapters. Connect 7 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Project Management — List all your active project folders, retrieve their specific IDs, and view sections within specific projects
Task Execution — View your complete list of pending tasks and mark them as completed instantly
Create Tasks — Add new items to a specific project or your inbox naturally in plain conversation
Organization — Look up available labels/tags to categorize your work
Collaboration — Read through existing comments to catch up on discussion history for any particular task

The Todoist MCP Server exposes 7 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Todoist to LangChain via MCP

Follow these steps to integrate the Todoist MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 7 tools from Todoist via MCP

Why Use LangChain with the Todoist MCP Server

LangChain provides unique advantages when paired with Todoist through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents — combine Todoist MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Todoist queries for multi-turn workflows

Todoist + LangChain Use Cases

Practical scenarios where LangChain combined with the Todoist MCP Server delivers measurable value.

RAG with live data: combine Todoist tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Todoist, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Todoist tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Todoist tool call, measure latency, and optimize your agent's performance

Todoist MCP Tools for LangChain (7)

These 7 tools become available when you connect Todoist to LangChain via MCP:

complete_task

Marks a task as completed

create_task

Provide content and an optional project ID. Creates a new task in Todoist

list_comments

Lists all comments for a specific task

list_labels

Lists all user-defined labels

list_projects

Lists all active projects in Todoist

list_sections

Lists all sections within a specific project

list_tasks

Can filter by project_id. Lists active tasks, optionally filtered by project

Example Prompts for Todoist in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Todoist immediately.

"Check all my active tasks and projects."

"Complete the task with ID 81229."

Troubleshooting Todoist MCP Server with LangChain

Common issues when connecting Todoist to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Todoist + LangChain FAQ

Common questions about integrating Todoist MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.