Todoist MCP Server Extended: Model Context Protocol Integration

Overview: What is Todoist MCP Server Extended?

Todoist MCP Server Extended is an advanced implementation of the Model Context Protocol (MCP) that seamlessly integrates Claude or any other MCP-compatible Large Language Model (LLM) with Todoist. This integration leverages everyday language to manage tasks, projects, and labels within Todoist, providing a powerful toolset for LLMs to interact with structured data in real-world applications.

🔧 Core Features & MCP Capabilities

Todoist MCP Server Extended offers a robust set of features designed to enhance the interaction between AI applications and task management systems. Key capabilities include:

Task Management: Create, update, complete, and delete tasks using natural language.
Label Management: Easily manage personal labels and task labels through intuitive commands.
Project Management: Create, update, and manage Todoist projects with precision.
Section Organization: Define and organize sections within projects for better clarity and workflow optimization.
Smart Search & Filtering: Quickly find tasks and labels using partial name matches or advanced filtering criteria.
Rich Task Details: Support for detailed task descriptions, due dates, priority levels, and assignment to specific projects/sections.
Batch Operations: Tools designed with batch operation support and custom parameters, ideal for LLM workflow efficiency.

These features not only simplify the interaction between AI applications but also optimize the overall user experience, making Todoist a dynamic and flexible resource within AI workflows.

⚙️ MCP Architecture & Protocol Implementation

MCP architecture in Todoist Server Extended revolves around defining clear communication channels between AI clients (like Claude Desktop) and various internal tools such as task management, label handling, and project organization. The protocol ensures seamless data exchange by standardizing input formats, response structures, and error handling.

A Mermaid diagram illustrates the flow of MCP Protocol:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

This diagram highlights the interaction between an AI application, MCP protocol, and the Todoist server, ensuring a robust and efficient data flow.

🚀 Getting Started with Installation

Installing Todoist MCP Server Extended is straightforward, whether you opt for Smithery or npm. Here's a step-by-step guide:

Installing via Smithery

Open your terminal (Windows PowerShell works fine).
Run the following command:
```
npx -y @smithery/cli install @Chrusic/todoist-mcp-server-extended --client claude
```
Note: The same command can be modified for other clients like cline or windsurf by changing the last parameter accordingly.

Installing via npm

Open your terminal and execute:

npm install -g @chrusic/todoist-mcp-server-extended

💡 Key Use Cases in AI Workflows

Todoist MCP Server Extended can be used in various AI workflows, enhancing productivity by integrating natural language processing with structured task management systems. Here are two practical use cases:

Use Case 1: Personal Project Management

AI applications like Claude Desktop can manage daily tasks and projects by interpreting user commands to create, update, or complete tasks within Todoist. For instance:

Task Creation: "Assign the 'Review PR' task under project 'Work' section 'To Do'."
Priority Setting: "Set high priority for task 'Documentation.'"

Use Case 2: Team Collaboration

In team environments, AI applications can help manage shared tasks and labels, promoting collaboration by:

Task Sharing & Assignment: "Add the 'Meeting Minutes' label to the task under project 'Internal Meetings'."
Progress Tracking: "List all tasks assigned to me for today's meeting."

🔌 Integration with MCP Clients

Todoist MCP Server Extended seamlessly integrates with various MCP clients, including:

Claude Desktop
Continue
Cursor (beta support)

The compatibility matrix provides a clear overview of supported clients and their features:

| MCP Client | Resources | Tools | Prompts |
|------------|-----------|-------|---------|
| Claude Desktop | ✅ | ✅ | ✅ | Full Support |
| Continue | ✅ | ✅ | ✅ | Full Support |
| Cursor | ❌ | ✅ | ❌ | Tools Only |

📊 Performance & Compatibility Matrix

This section outlines the performance and compatibility of Todoist MCP Server Extended, ensuring smooth operation across different environments.

Todoist MCP Server Extended is designed to work effectively with a wide range of API tokens from Todoist. The server utilizes efficient data processing algorithms to handle large datasets seamlessly.

🛠️ Advanced Configuration & Security

Configuring Todoist MCP Server Extended involves setting up the API token and ensuring secure connections between the MCP clients and the server. Here’s an example configuration snippet:

{
  "mcpServers": {
    "todoist": {
      "command": "npx",
      "args": ["-y", "@chrusic/todoist-mcp-server-extended"],
      "env": {
        "TODOIST_API_TOKEN": "PASTE-YOUR-API-TOKEN-HERE"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

Q1: What is the difference between Claude Desktop and Continue in terms of Todoist MCP Server Extended compatibility?

A1: Both Claude Desktop and Continue offer full support through Todoist MCP Server Extended. There are no differences; both can leverage its capabilities seamlessly.

Q2: Can I use multiple API tokens with this server to manage different Todoist accounts simultaneously?

A2: Yes, you can configure the server to work with multiple API tokens by adding separate entries in your claude_desktop_config.json file. Each entry should include a unique environment variable for each account.

Q3: How does the batch operation feature contribute to AI application efficiency?

A3: The batch operations feature allows clustering of similar tasks and labels, reducing redundancy and increasing workflow speed. This is particularly useful in scenarios where users need to process large volumes of data or commands quickly.

Q4: Is it possible to add custom triggers for certain events within Todoist using this server?

A4: Currently, the integration does not support adding custom triggers directly. However, users can utilize existing command capabilities to create personalized workflows that trigger on specific conditions.

Q5: Can I replace all the tool commands with my own custom tools and logic through this server?

A5: While the base MCP framework adheres to common standards, flexibility options allow for user-defined extensions or replacements of certain tools. Custom plugins can be developed using the provided APIs.

👨‍💻 Development & Contribution Guidelines

Contributions are welcomed if you identify improvements or encounter issues. The guidelines stipulate how to submit pull requests effectively and ensure code quality remains high.

🌐 MCP Ecosystem & Resources

Explore other powerful tools and resources within the broader MCP ecosystem for more comprehensive AI integrations:

By positioning Todoist MCP Server Extended as a key component of the MCP ecosystem, we enable developers to build more robust and flexible AI applications.

Todoist MCP Server Extended