Todoist MCP Server

The Abhiz123 Todoist MCP Server bridges the gap between conversational AI and task management by allowing Claude to read, create, update, and delete tasks in a Todoist account using natural language. Instead of relying on manual API calls or command‑line interfaces, developers can embed a single MCP endpoint into their AI workflows and let the assistant handle everyday task‑management conversations. This eliminates friction for users who prefer talking to their AI over typing commands, while keeping the full power of Todoist’s filtering and metadata features.

At its core, the server exposes a set of intuitive tools that mirror common Todoist operations: , , , , and . Each tool accepts plain‑English prompts, parses them for task attributes or search terms, and translates the intent into Todoist API calls. For example, a user can say “Create high priority task ‘Fix bug’ with description ‘Critical performance issue’” and the server will translate that into a properly formatted request to Todoist. The natural‑language parsing layer is designed to be forgiving, supporting partial name matches and date expressions like “tomorrow” or “next Monday,” which makes the assistant feel conversational rather than mechanical.

Key capabilities include smart task search—the server can locate tasks by partial names or dates—and flexible filtering, allowing users to retrieve tasks filtered by due date, priority, project, or any combination of attributes. The tool set also supports rich task details such as descriptions and priority levels, ensuring that the assistant can create or update tasks with full context. Error handling is intentionally clear: when a task cannot be found or an API call fails, the assistant returns concise feedback that can be relayed back to the user, maintaining a smooth conversational loop.

Real‑world use cases span from solo developers who want to keep track of sprint stories in a chat, to teams that use Claude as a project management companion. A product manager could ask “Show all high‑priority tasks due this week” and immediately receive a list, while a developer might say “Mark the PR review task as complete” to close out work without leaving the chat. Because the server operates through MCP, it integrates seamlessly with any Claude‑compatible environment—desktop clients, web interfaces, or custom integrations—making it a versatile addition to AI‑driven productivity stacks.

What sets this server apart is its developer-friendly design. It requires only a Todoist API token and can be launched via a single command, with environment variables handling authentication. The MCP interface abstracts away the complexities of Todoist’s REST API, letting developers focus on crafting conversational flows rather than managing HTTP requests. This lightweight yet powerful solution empowers AI assistants to become true task‑management partners, enhancing productivity with minimal friction.