Google Tasks MCP Server

The Google Tasks MCP Server bridges the gap between AI assistants and Google’s task‑management ecosystem by exposing the Google Tasks API through the Model Context Protocol (MCP). This allows developers to embed task creation, retrieval, and management directly into AI‑driven workflows—whether they’re building a personal productivity bot, integrating with an IDE like Cursor, or creating custom voice assistants. By turning Google Tasks into a first‑class MCP resource, the server eliminates the need for separate OAuth flows or custom SDKs; the AI client simply sends MCP calls and receives structured JSON responses.

Why It Matters

Task management is a foundational component of many productivity pipelines. Traditionally, developers had to write bespoke authentication code and handle API pagination manually. The MCP server abstracts these complexities: it manages OAuth 2.0 tokens, refreshes them automatically, and presents a clean set of tools that mirror the Google Tasks REST endpoints. For AI assistants, this means instant access to a user’s task lists without leaking credentials or requiring additional configuration steps. It also opens the door for richer conversational experiences—an assistant can ask, “What’s on my today list?” and retrieve real‑time data through a single MCP call.

Key Features

• Task List Discovery – returns all task lists belonging to the authenticated user, allowing an AI assistant to present or filter options contextually.
• Task Retrieval – fetches tasks within a specific list, supporting filtering by status or due date.
• Task Creation – lets an assistant add new items, complete with title, notes, and due dates, directly from a conversation.
• Completion & Deletion – and enable state changes, letting users manage tasks without leaving the chat interface.
• Automatic Token Management – The server handles OAuth token persistence () and refreshes credentials transparently, so developers can focus on building logic rather than authentication plumbing.

Real‑World Use Cases

• Personal Productivity Bots – A user can say, “Add a grocery list item for milk,” and the assistant creates it in Google Tasks.
• Project Management Extensions – Teams can use an AI assistant to pull up sprint task lists, update progress, or close tasks directly from their IDE.
• Voice‑Controlled Scheduling – Integration with smart speakers can let users manage tasks hands‑free, while the MCP server ensures secure access.
• Workflow Automation – Combine with other MCP servers (e.g., calendar, email) to trigger task creation when an event is added or a mail arrives.

Integration with AI Workflows

The server exposes its tools via MCP, so any client that understands the protocol—such as Cursor or custom AI agents—can register it in a simple JSON configuration. Once registered, the client can invoke , , or any other tool with a single function call, receiving typed JSON responses that can be parsed or displayed directly. This tight coupling means developers can prototype complex assistant behaviors rapidly, relying on the MCP server to handle all Google‑specific details.

Unique Advantages

• Zero-Code Authentication – The OAuth dance is handled once during startup; subsequent calls use cached tokens.
• Consistent API Surface – The MCP tool names mirror the Google Tasks REST endpoints, reducing cognitive load for developers familiar with the API.
• Extensibility – The server’s modular design allows adding more Google Tasks features (e.g., task parents, reminders) without altering the client side.
• Open Source Learning Platform – Built as a learning exercise, it serves as a reference implementation for developers looking to write their own MCP servers.

In summary, the Google Tasks MCP Server transforms a complex third‑party API into an accessible, AI‑friendly service that empowers developers to embed task management seamlessly into conversational and IDE workflows.