Todoist MCP Server Integration

What does “Todoist” MCP Server do?

The Todoist MCP Server is a Model Context Protocol (MCP) server that integrates with Todoist, enabling AI assistants like Claude to manage tasks using natural language. It acts as a bridge between AI models and the Todoist API, allowing users to create, update, complete, delete, and search tasks with everyday language. The server facilitates enhanced productivity workflows by making task management more intuitive and accessible, supporting features such as smart task search, flexible filtering, and rich task details. By leveraging the Todoist MCP Server, developers can empower AI assistants to handle complex task management operations seamlessly, streamlining personal and team productivity.

List of Prompts

No prompt templates are mentioned in the repository.

List of Resources

No explicit resources are documented in the repository.

List of Tools

• todoist_create_task
  Create new tasks with attributes such as title, description, due date, and priority. Supports natural language input for seamless task creation.

• todoist_get_tasks
  Retrieve and filter tasks by due date, priority, or project. Allows natural language date filtering and result limits.

• todoist_update_task
  Update existing tasks using partial name matching and natural language. Modify attributes like content, description, due date, and priority.

• todoist_complete_task
  Mark tasks as complete using natural language search and partial name matching. Confirms completion status.

• todoist_delete_task
  Delete tasks found by name with natural language search and confirmation messaging.

Use Cases of this MCP Server

• Natural Language Task Management
  Enables users to create, update, complete, and delete tasks in Todoist by simply describing their intent in everyday language, reducing friction and improving productivity.

• Smart Task Search
  AI assistants can retrieve and filter tasks based on attributes such as due date, priority, or project, making it easier for users to find relevant tasks quickly.

• Flexible Filtering and Bulk Operations
  Supports batch operations and advanced filtering (e.g., high priority tasks due this week), streamlining the management of large task lists.

• Seamless Integration with AI Assistants
  Allows AI models to interact directly with Todoist, making it possible to build conversational or workflow-driven productivity tools.

• Enhanced Developer Workflows
  Developers can integrate Todoist task management into custom applications or broader workflow automation systems using MCP.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Access your Windsurf configuration file.
3. Add the Todoist MCP Server under the mcpServers section:

   {
     "mcpServers": {
       "todoist": {
         "command": "npx",
         "args": ["-y", "@abhiz123/todoist-mcp-server"],
         "env": {
           "TODOIST_API_TOKEN": "your_api_token_here"
         }
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the MCP server is running and accessible.

Claude

1. Install Node.js if not already installed.
2. Locate your claude_desktop_config.json.
3. Add the Todoist MCP Server configuration:

   {
     "mcpServers": {
       "todoist": {
         "command": "npx",
         "args": ["-y", "@abhiz123/todoist-mcp-server"],
         "env": {
           "TODOIST_API_TOKEN": "your_api_token_here"
         }
       }
     }
   }
   

4. Save the file and restart Claude Desktop.
5. Confirm the server is available in Claude.

Cursor

1. Install Node.js.
2. Open Cursor’s configuration file (usually a JSON file).
3. Insert the Todoist MCP Server under mcpServers:

   {
     "mcpServers": {
       "todoist": {
         "command": "npx",
         "args": ["-y", "@abhiz123/todoist-mcp-server"],
         "env": {
           "TODOIST_API_TOKEN": "your_api_token_here"
         }
       }
     }
   }
   

4. Save and restart Cursor.
5. Ensure the MCP server is active.

Cline

1. Install Node.js.
2. Edit your Cline configuration file.
3. Add the following to the mcpServers section:

   {
     "mcpServers": {
       "todoist": {
         "command": "npx",
         "args": ["-y", "@abhiz123/todoist-mcp-server"],
         "env": {
           "TODOIST_API_TOKEN": "your_api_token_here"
         }
       }
     }
   }
   

4. Save the configuration and restart Cline.
5. Check that the Todoist MCP Server is available for use.

Securing API Keys

Store sensitive tokens like TODOIST_API_TOKEN securely using environment variables within the configuration:

{
  "mcpServers": {
    "todoist": {
      "command": "npx",
      "args": ["-y", "@abhiz123/todoist-mcp-server"],
      "env": {
        "TODOIST_API_TOKEN": "your_api_token_here"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "todoist": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “todoist” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Between the available documentation and features, the Todoist MCP Server provides robust task management tools and clear setup instructions but lacks prompt and resource documentation. Sampling and Roots are not mentioned. Overall, this MCP is well-suited for task automation but could benefit from expanded documentation.

MCP Score