About Google Calendar MCP Server
Google Calendar MCP Server lets LLM applications manage Google Calendar data. It supports calendar and event listing, event creation, updates, and deletion.
Key features
- 01List available calendars
- 02List calendar events
- 03Create calendar events
- 04Update existing events
- 05Delete events
Use cases
- 01Find events in a selected calendar
- 02Create a calendar event
- 03Update or delete an event
MCP support
An MCP server that exposes Google Calendar calendar and event operations to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGoogle Calendar MCP Server
This is a Model Context Protocol (MCP) server that provides integration with Google Calendar. It allows LLMs application manage calendar events through a standardized interface.
Features
- List available calendars
- List events from a calendar
- Create new calendar events
- Update existing events
- Delete events
Google Cloud Setup
- Go to the Google Cloud Console
- Create a new project or select an existing one.
- Enable the Google Calendar API.
- Create OAuth 2.0 credentials:
- Go to Credentials
- Click "Create Credentials" > "OAuth client ID"
- Choose "User data" as the type of data the app will be accessing.
- Add your app name and contact information.
- Add the following scope (optional):
https://www.googleapis.com/auth/calendar.events
- Select "Desktop app" as the application type.
- Add your email address as a test user under the OAuth Consent screen.
- Note: It may take a few minutes for the test user to propagate.
Installation
Steps
- Clone the repository:
git clone <repository-url> cd gcal-mcp-server - Create a virtual environment:
uv venv # On Mac / linux source .venv/bin/activate # On Windows .venv\Scripts\activate # Install package in editable mode uv pip install -e .
Usage
- Set up the
.envfile with the required environment variables for LLMs. - Run the server:
uv run client.py
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.