Google Tasks MCP

Google Tasks MCP

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A1 Google Tasks MCP lets an AI app manage Google Tasks in plain language. Plan a project as a task list, break work into subtasks with due dates and notes, mark things done and keep everything in order.

It uses the Google Tasks API with your Google account. It separates reversible completion from permanent deletion and makes the limits of the Tasks API explicit instead of implying that every to-do feature is possible.

• 21 tools. List, create and update task lists and tasks, move tasks, manage completion, sweep finished work and reach the raw API when a dedicated tool is missing.
• Connects from the conversation. Say "connect Google Tasks": the server walks you through the OAuth client, catches Google's redirect on 127.0.0.1 with PKCE and keeps the tokens itself — no config files, no restart.
• Completion is reversible, deletion is not. complete_task has an undo (reopen_task); the delete tools are separate and marked destructive.
• Due dates are honest. The API stores only the calendar date — the server never pretends to schedule a time of day; times belong in the notes.
• Minimal Google scope. A single tasks scope, without Drive, Calendar or Gmail access.

Start with a read-only question:

Show me my task lists and everything due before Friday in my default list.

Connect the server · Explore use cases · Open technical documentation

See it work in a minute

You: What's still open in the "Website launch" list, and what's due this week?

Assistant: Shows the open tasks with their due dates, notes and subtasks. Nothing changes.

You: Add a task "Send the launch announcement" due Friday as a subtask of "Marketing".

Assistant: Shows the target list, the parent task and the proposed task, then asks for confirmation before creating it.

You: Confirm.

Assistant: Creates the subtask with a Friday due date. It does not complete or delete anything unless you ask separately.

Contents

• Quick start
• What you can ask it to do
• How a task changes
• What can change
• Getting access
• Configuration
• Data, limits and background work
• Technical documentation
• Support

Quick start

You need Node.js 20+ and a Google account. Credentials are not required at install time — the server connects from the conversation.

1. Add the server to your AI app.
2. Say "connect Google Tasks": the assistant walks you through creating the OAuth client and approving access without editing config files.
3. Ask the read-only question above.

Codex

In the app: open Settings → MCP servers, select Add server, choose STDIO, enter the command npx -y mcp-google-tasks@latest and environment variables GOOGLE_TASKS_CLIENT_ID, GOOGLE_TASKS_CLIENT_SECRET, GOOGLE_TASKS_REFRESH_TOKEN, then select Save and Restart.

From the command line:

codex mcp add google-tasks \

-- npx -y mcp-google-tasks@latest

codex mcp list

Codex MCP documentation

Claude Code

claude mcp add \

--transport stdio --scope user google-tasks \ -- npx -y mcp-google-tasks@latest

claude mcp list

Claude Code MCP documentation

Claude Desktop

The current official path is Settings → Extensions. For a custom desktop extension, open Advanced settings → Extension Developer → Install Extension…, select a .mcpb file and follow the prompts.

This repository currently publishes an npm stdio package and does not contain a .mcpb bundle. For Claude Desktop builds that still support local configuration, use the following JSON stdio configuration as a fallback:

{

"mcpServers": { "google-tasks": { "command": "npx", "args": ["-y", "mcp-google-tasks@latest"] } } }

In those builds, save it to ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows.

Claude Desktop MCP documentation

Cursor

Add this to ~/.cursor/mcp.json on macOS/Linux or %USERPROFILE%\.cursor\mcp.json on Windows:

{

"mcpServers": { "google-tasks": { "type": "stdio", "command": "npx", "args": ["-y", "mcp-google-tasks@latest"] } } }

Cursor MCP documentation

VS Code

Run MCP: Open User Configuration and add:

{

"servers": { "google-tasks": { "type": "stdio", "command": "npx", "args": ["-y", "mcp-google-tasks@latest"] } } }

Check it with MCP: List Servers.

VS Code MCP documentation

What you can ask it to do

See your lists and plan the day

• Show my task lists and the open tasks in each one.
• What's due this week in the default list? Include subtasks.
• What changed since yesterday? Include completed and hidden tasks.

Create and organize work

• Create a "Website launch" list with tasks for design, content and QA.
• Add a task due Friday with notes, nested under the "Marketing" task.
• Move a task to the top of the list, under another task, or into a different list.

Track completion

• Mark the review task done — and reopen it if the work comes back.
• Sweep every completed task out of the list view in one go.
• Show the hidden tasks that were swept earlier.

How a task changes

1. Tasks live in task lists. Every account has a built-in default list, addressed by the special id @default; create_tasklist adds more.
2. A task carries a title, notes and a date-only due date — the API discards the time portion, so a time of day belongs in the notes.
3. Ordering and nesting change only through move_task; the API's position field is read-only.
4. Completing a task is reversible: reopen_task brings it back. Deleting a task or a list is permanent, and deleting a list removes every task in it.

Recurring tasks cannot be created through the API. Tasks assigned from Google Docs or Chat can be read but not created or moved to another list, and deleting one also removes it in the originating document. There is no server-side search or sorting — the server lists tasks and the AI client filters them.

What can change

The AI client controls confirmation prompts. The server marks reads, writes and destructive tools so the client can distinguish an inspection from a live change.

Getting access

Google Tasks requires OAuth 2.0; an API key is not enough. There are two ways in, and the first one needs no configuration files.

Connect from the chat (recommended)

Say "connect Google Tasks" and the assistant runs the flow with you:

1. setup_instructions prints the checklist: create or select a Google Cloud project, enable Google Tasks API, configure the consent screen and create a Desktop app OAuth client.
2. Download that client's JSON ("Download JSON") and give the assistant its path — set_client stores it owner-only. The secret never goes through the conversation.
3. start_login returns a Google consent link. Open it on this machine and approve; the code comes back to a one-shot listener on 127.0.0.1 (PKCE), never through the chat.
4. finish_login exchanges the code and saves the tokens to ~/.config/mcp-google-tasks/credentials.json (mode 0600) and verifies them with a real Google Tasks API call — so an API that is still switched off is caught right there.

The tokens are re-read on every call, so the connection works immediately — no restart of the AI app. auth_status shows what is connected, logout revokes and deletes it.

Environment variables (CI, unattended installs)

1. Create or select a Google Cloud project and enable Google Tasks API.
2. Configure the OAuth consent screen and create a Desktop app OAuth client.
3. Authorize the Google account that owns the tasks. The OAuth 2.0 Playground can obtain the refresh token when Use your own OAuth credentials is enabled.
4. Request the scope:

   https://www.googleapis.com/auth/tasks

Testing-mode OAuth refresh tokens can expire after seven days. Publish the OAuth app, or use an Internal app in a Workspace domain, when you need long-lived access. Treat the client secret and refresh token as passwords.

Configuration

Every variable is optional — with none of them the server connects from the chat.

\* Provide either the OAuth trio or an access token.

Without credentials the server still starts and completes the MCP handshake; the first tool call then fails with a message naming the variables to set and asking for a restart.

Data, limits and background work

• Requests go to Google Tasks. The local server refreshes Google OAuth tokens and calls the Tasks API. Its anonymous telemetry contains an installation ID, package version, AI client and platform versions, and tool names — never OAuth tokens, task content, tool arguments or prompts. For each tool call it also sends the outcome and, on failure, an excerpt of the error text with e-mails, addresses, token