Overview

The mcp-server-todoist is an MCP (Model Context Protocol) server that bridges the gap between AI assistants and the Todoist task‑management platform. By exposing a set of resources, tools, prompts, and sampling endpoints, it lets an AI client (such as Claude) query, create, update, or delete tasks directly from Todoist. This eliminates the need for manual API calls and provides a natural, conversational interface to a widely used productivity tool.

Problem Solved

Developers building AI‑powered workflows often need to integrate external task management systems. Without a dedicated MCP server, each integration requires custom authentication handling, REST‑API wrappers, and state management. This can become repetitive and error‑prone, especially when multiple assistants or services need to interact with Todoist. The mcp-server-todoist centralizes this logic, providing a single, well‑defined contract that any MCP client can consume. It removes boilerplate code and standardizes how tasks are referenced, retrieved, and modified.

What the Server Does

At its core, the server offers a set of resources that mirror Todoist’s entities—projects, tasks, labels, and comments. For each resource, the server implements CRUD operations through MCP tools. When an AI client invokes a tool such as or , the server authenticates with Todoist using a secure token, translates the request into the appropriate API call, and returns a structured response. Additionally, the server provides prompt templates that help an assistant frame user intent into tool calls, ensuring consistent parameter usage and reducing ambiguity.

Key Features & Capabilities

• Unified Authentication: Handles OAuth or API token management transparently, so the AI client never deals with credential storage.
• Rich Query Language: Supports filtering by project, label, due date, or priority through intuitive tool arguments.
• Contextual Updates: Allows partial updates (e.g., changing only the due date) without needing to resend entire task objects.
• Batch Operations: Exposes tools for bulk creation or deletion, improving efficiency when managing large task lists.
• Error Normalization: Converts Todoist’s error responses into standardized MCP error objects, making downstream handling predictable.

Use Cases & Real‑World Scenarios

• Conversational Task Management: A user asks the assistant to “add a follow‑up task for tomorrow” and the assistant creates it instantly in Todoist.
• Dynamic Reporting: An AI pulls all high‑priority tasks, summarizes them, and emails a weekly digest to the team.
• Workflow Automation: Integrate with other MCP servers (e.g., calendar, email) so that when an event is added, a corresponding Todoist task appears automatically.
• Team Collaboration: Multiple assistants can sync updates to shared projects, ensuring everyone sees the latest status without manual refreshes.

Integration with AI Workflows

Because MCP servers follow a standard interface, any Claude or other AI client that supports MCP can consume this server with minimal configuration. The assistant’s natural language processing engine maps user queries to the appropriate tool calls, passing arguments in a structured format. The server’s responses feed back into the assistant’s context, enabling multi‑turn conversations that build on previous actions. This tight coupling allows developers to craft sophisticated, end‑to‑end AI applications that feel seamless and intuitive.

By encapsulating Todoist’s functionality behind a clean MCP contract, mcp-server-todoist empowers developers to build AI assistants that can manage tasks effortlessly, focus on user intent, and deliver real productivity gains.