Todoist MCP Server

Todoist MCP Server

The Todoist MCP Server bridges the gap between AI assistants and the Todoist task‑management platform. By exposing a Model Context Protocol interface, it lets an assistant fetch, create, update, and delete tasks or projects without needing to embed Todoist’s API logic directly into the assistant’s code. This is especially valuable for developers building AI‑powered productivity tools who want a clean, standardized way to interact with a widely used task manager.

The server implements a comprehensive set of Todoist operations. For tasks it supports filtering by label, project, due date and more; retrieving task details; creating new items with optional assignees or priorities; updating fields such as description, due date or project assignment; marking items complete; and removing them. For projects it offers listing all available projects and fetching individual project details. Each operation is wrapped in an MCP endpoint, so a client can query for capabilities and then call the appropriate tool with well‑defined arguments. The server also provides filter rules and example filters, giving assistants a ready reference for how to construct queries.

Key capabilities include:

• Standardized task and project CRUD that abstracts the underlying HTTP calls to Todoist.
• Filter rule exposition, enabling assistants to suggest or generate complex queries.
• Dual‑mode operation: an HTTP server for simple web hooks or a stdio mode that plugs directly into MCP clients such as Claude.
• Environment‑driven configuration via the variable, keeping secrets out of code.

Typical use cases are:

• A virtual assistant that can read a user’s inbox and automatically create tasks.
• An AI‑driven project manager that can pull all overdue items, suggest prioritization, and update statuses.
• A chatbot integrated into a collaboration platform that can list projects or fetch task details on demand.

Integrating the server into an AI workflow is straightforward. A developer deploys the MCP server (as a Docker container or binary), configures the API token, and then registers its capabilities with an MCP‑compliant assistant. The assistant can query the server’s capability set, invoke tools such as or , and receive structured JSON responses that the assistant can display or further process. Because MCP standardizes the request/response format, adding new Todoist features later requires only a small server update and no changes to the assistant’s logic.

What sets this MCP server apart is its focus on completeness and simplicity. It covers all common Todoist operations in a single, well‑documented service while keeping the deployment model flexible. For developers looking to give AI assistants robust task‑management power without wrestling with OAuth flows or API rate limits, the Todoist MCP Server provides a ready‑to‑use, production‑grade bridge to one of the most popular productivity platforms.