UBOS Asset Marketplace: Todoist MCP Server - Your Gateway to AI-Powered Task Management

In the rapidly evolving landscape of productivity and task management, the integration of AI is no longer a futuristic concept but a present-day necessity. At UBOS, we understand this shift and are committed to providing you with cutting-edge tools that seamlessly blend AI capabilities with your existing workflows. This is why we are excited to feature the Todoist MCP Server on our Asset Marketplace – an open-source solution that revolutionizes how you interact with Todoist, one of the most popular task management applications.

What is an MCP Server?

Before diving into the specifics of the Todoist MCP Server, let’s first understand the underlying technology: the Model Context Protocol (MCP). MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). Imagine MCP as a universal translator, allowing AI models to access and interact with external data sources and tools. An MCP server acts as a bridge, enabling AI models to retrieve information, trigger actions, and automate processes within different applications.

The Todoist MCP Server: Bridging the Gap Between AI and Task Management

The Todoist MCP Server is a Python-based open-source implementation of an MCP server specifically designed for interacting with Todoist. It leverages the fastmcp library and the todoist-api-python library to provide a robust and efficient interface for managing your Todoist tasks through natural language commands. This means you can use AI tools like Claude Desktop or Cursor to create, read, update, and delete tasks, projects, sections, labels, and comments in Todoist – all with the power of natural language processing.

Key Features and Functionalities

• Comprehensive Todoist Integration: The server offers a complete suite of tools for managing every aspect of your Todoist account, from creating simple tasks to managing complex projects.
• Natural Language Command Support: Interact with Todoist using natural language prompts through your favorite MCP-compatible client (e.g., Claude Desktop, Cursor).
• Filtering and Pagination: Efficiently fetch data from Todoist with advanced filtering and pagination options.
• Multiple Transport Options: Supports both stdio and SSE (Server-Sent Events) transport for seamless MCP communication.
• Open-Source and Customizable: The server is open-source, allowing you to customize and extend its functionality to meet your specific needs.

Recommended Use Cases: Unleashing the Power of AI in Your Workflow

The Todoist MCP Server opens up a world of possibilities for automating and streamlining your task management workflow. Here are some recommended use cases to get you started:

• AI-Powered Time Blocking: Combine the Todoist MCP Server with a calendar MCP (e.g., Google Calendar) to automatically time-block your tasks based on your availability, deadlines, and priority levels. Let AI handle the scheduling, so you can focus on execution.
• Automated Task Creation from Emails: Integrate the server with an email MCP to automatically generate and schedule tasks in Todoist based on incoming emails. This is particularly useful for managing notifications from platforms like Canvas or automatically scheduling homework assignments.
• Collaborative Project Planning: Use the server to vibe-plan a sectioned project plan with actionable, assigned tasks and descriptions that you can easily share with your team members. Foster collaboration and ensure everyone is on the same page.

Installation and Configuration: Getting Started with the Todoist MCP Server

Setting up the Todoist MCP Server is straightforward, especially with the recommended Smithery CLI. Smithery simplifies the process of discovering, installing, and managing MCP servers. Here’s a quick overview:

1. Prerequisites:

   • A valid Todoist account.
   • Your Todoist API token (found in Todoist Settings -> Integrations -> Developer API Token).
   • Python 3.12 or higher.
   • A package manager (uv or pip with venv/conda).

2. Installation via Smithery CLI:

   • Install Smithery CLI: npm install -g @smithery/cli
   • Install the Todoist MCP Server: npx -y @smithery/cli install @koji0701/todoist-mcp-server --client <your_client_name> (replace <your_client_name> with your MCP client, e.g., claude, cursor).

3. Configuration:

   • Provide your Todoist API token during the Smithery installation process or set it as an environment variable (TODOIST_API_KEY or TODOIST_TOKEN).

How UBOS Enhances the Todoist MCP Server Experience

While the Todoist MCP Server is a powerful tool on its own, integrating it with the UBOS platform unlocks even greater potential. UBOS provides a full-stack AI Agent development platform, enabling you to:

• Orchestrate AI Agents: Seamlessly integrate the Todoist MCP Server with other AI agents within the UBOS platform to create complex, automated workflows.
• Connect to Enterprise Data: Connect the server to your enterprise data sources, allowing AI agents to access and utilize relevant information for task management.
• Build Custom AI Agents: Leverage the UBOS platform to build custom AI agents tailored to your specific needs and integrate them with the Todoist MCP Server.
• Multi-Agent Systems: Create sophisticated multi-agent systems that leverage the Todoist MCP Server for task management as part of a larger, coordinated effort.

In essence, UBOS provides the infrastructure and tools necessary to take the Todoist MCP Server to the next level, transforming it from a standalone tool into a core component of your AI-powered productivity ecosystem.

Diving Deeper: Exploring the Available MCP Tools

The Todoist MCP Server exposes a rich set of tools under the todoist namespace, allowing you to perform virtually any operation within your Todoist account. Here’s a breakdown of the available tool categories:

• Tasks:

  • add_task: Create a new task.
  • get_task: Get a specific task by its ID.
  • get_tasks: Get active tasks, optionally filtered.
  • filter_tasks: Get active tasks matching a filter query.
  • add_task_quick: Create a new task using Todoist’s Quick Add syntax.
  • update_task: Update an existing task.
  • complete_task: Complete a task (maps to close_task).
  • uncomplete_task: Uncomplete a task (maps to reopen_task).
  • move_task: Move a task to a different project or section (via update_task).
  • delete_task: Delete a task.
  • get_completed_tasks_by_due_date: Get completed tasks within a due date range.
  • get_completed_tasks_by_completion_date: Get completed tasks within a completion date range.

• Projects:

  • add_project: Create a new project.
  • get_project: Get a project by its ID.
  • get_projects: Get all active projects.
  • update_project: Update an existing project.
  • archive_project: Archive a project.
  • unarchive_project: Unarchive a project.
  • delete_project: Delete a project.
  • get_collaborators: Get collaborators in a shared project.

• Sections:

  • add_section: Create a new section within a project.
  • get_section: Get a specific section by its ID.
  • get_sections: Get all active sections, optionally filtered by project.
  • update_section: Update an existing section’s name.
  • delete_section: Delete a section.

• Labels:

  • add_label: Create a new personal label.
  • get_label: Get a specific personal label by its ID.
  • get_labels: Get all personal labels.
  • update_label: Update a personal label.
  • delete_label: Delete a personal label.
  • get_shared_labels: Get shared labels.
  • rename_shared_label: Rename a shared label (finds by name, updates by ID).
  • remove_shared_label: Remove a shared label (finds by name, deletes by ID).

• Comments:

  • add_comment: Create a new comment on a task or project.
  • get_comment: Get a specific comment by its ID.
  • get_comments: Get comments for a task or project.
  • update_comment: Update an existing comment’s content.
  • delete_comment: Delete a comment.

This comprehensive set of tools provides you with granular control over your Todoist account, enabling you to automate even the most complex task management workflows.

The Future of Task Management: Embracing AI with UBOS and the Todoist MCP Server

The Todoist MCP Server represents a significant step forward in the evolution of task management. By leveraging the power of AI and the flexibility of the MCP protocol, this server empowers you to work smarter, not harder. At UBOS, we are committed to providing you with the tools and resources you need to thrive in the age of AI. Explore the Todoist MCP Server on our Asset Marketplace today and discover how AI can transform your productivity.

With the Todoist MCP server and UBOS platform, you are not just managing tasks; you are orchestrating your success.

Contributing to the Project

The Todoist MCP Server is an open-source project, and contributions are highly encouraged. Whether you’re a seasoned developer or just starting out, there are many ways to contribute:

• Bug Reports: Report any bugs or issues you encounter while using the server.
• Feature Requests: Suggest new features or improvements to the server’s functionality.
• Code Contributions: Submit pull requests with bug fixes, new features, or performance enhancements.
• Documentation: Help improve the documentation by adding examples, clarifying explanations, or fixing errors.

By contributing to the project, you can help make the Todoist MCP Server even better for everyone.

License

The Todoist MCP Server is distributed under the MIT License, a permissive open-source license that grants you the freedom to use, modify, and distribute the software for any purpose. See the LICENSE file for more information.

Conclusion

The Todoist MCP Server is a valuable asset for anyone looking to integrate AI into their task management workflow. Its comprehensive feature set, ease of use, and open-source nature make it an ideal choice for both individual users and organizations. By leveraging the power of AI, you can automate tasks, streamline processes, and ultimately achieve greater productivity. Explore the Todoist MCP Server on the UBOS Asset Marketplace today and unlock the future of task management.