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Todoist MCP Server for LangChainGive LangChain instant access to 12 tools to Complete Task, Create Project, Create Task, and more

Built by Vinkius GDPR 12 Tools Framework

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

Ask AI about this App Connector for LangChain

The Todoist app connector for LangChain is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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-extended": {
            "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())
Todoist
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Todoist MCP Server

Connect your Todoist account to any AI agent and simplify how you organize your life and work through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Todoist through native MCP adapters. Connect 12 tools via 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

  • Task Control — Create, update, and complete tasks with full support for due dates, priorities, and descriptions.
  • Project Oversight — List all your projects and manage sections to keep your workflows structured.
  • Smart Filtering — Query your tasks using Todoist's powerful filter syntax (e.g., 'today', 'p1') via AI.
  • Categorization — List and manage labels to tag your tasks across different projects.
  • Collaboration — List comments on tasks and projects to track discussions and notes.
  • Workspace Maintenance — Reopen completed tasks or fetch detailed metadata for specific to-do items.

The Todoist MCP Server exposes 12 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.

All 12 Todoist tools available for LangChain

When LangChain connects to Todoist through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-management, to-do-list, workflow-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

complete_task

Mark a task as finished

create_project

Create a new project

create_task

Add a new to-do item

get_project_details

Get metadata for a project

get_task_details

Get details for a specific task

list_active_tasks

Can filter by project, label, or filter. List active tasks

list_all_labels

List your personal labels

list_comments

List comments for a task or project

list_project_sections

List sections within a project

list_projects

List your Todoist projects

reopen_task

Mark a closed task as active

update_task_details

Modify an existing task

Connect Todoist to LangChain via MCP

Follow these steps to wire Todoist into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 12 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.

01

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

02

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

03

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

04

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.

01

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

02

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

03

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

04

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

Example Prompts for Todoist in LangChain

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

01

"What are my high priority tasks for today?"

02

"Create a task in the 'Work' project: 'Submit expense report' due Friday at 5pm."

03

"Show me all active tasks with the label '@errand'."

Troubleshooting Todoist MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Todoist + LangChain FAQ

Common questions about integrating Todoist MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.