Google Calendar MCP Server
Integrates Google Calendar with AI assistants via MCP, enabling calendar listing and event CRUD operations.
README
Google Calendar MCP Server Tutorial
A tutorial project demonstrating how to build a Model Context Protocol (MCP) server that integrates with Google Calendar. This server exposes Google Calendar functionality as tools that AI assistants can use.
Note: This is an educational project for learning MCP server development. It is not intended for production use.
Table of Contents
- Overview
- Prerequisites
- Project Structure
- Setup
- Available Tools
- Architecture
- Configuration
- Tech Stack
Overview
This MCP server provides AI assistants with the ability to:
- List and manage calendars
- Create, read, update, and delete calendar events
- Query events with filters (time range, search terms, etc.)
Built with FastMCP for the MCP server implementation and the Google Calendar API for calendar operations.
Prerequisites
- Python 3.12 or higher
- uv package manager
- A Google Cloud project with Calendar API enabled
- OAuth 2.0 credentials (Desktop app type)
Project Structure
google-calendar-mcp-server-tutorial/
├── main.py # MCP server entry point
├── config.py # Configuration management
├── auth.py # Google OAuth2 authentication
├── logger.py # Logging utilities
├── service_factory.py # Factory for Google API services
├── models/ # Pydantic request models
│ ├── calendar/ # Calendar metadata models
│ ├── calendars_list/ # Calendar list models
│ └── event/ # Event operation models
├── services/ # Google Calendar API service layer
│ ├── calendar_service.py
│ ├── calendar_list_service.py
│ └── event_service.py
└── tools/ # MCP tool definitions
├── calendar.py
├── calendar_list.py
└── event.py
Setup
1. Clone the Repository
git clone <repository-url>
cd google-calendar-mcp-server-tutorial
2. Install Dependencies
uv sync
3. Configure Google Cloud
- Go to the Google Cloud Console
- Create a new project or select an existing one
- Enable the Google Calendar API:
- Navigate to "APIs & Services" > "Library"
- Search for "Google Calendar API" and enable it
- Create OAuth 2.0 credentials:
- Go to "APIs & Services" > "Credentials"
- Click "Create Credentials" > "OAuth client ID"
- Select "Desktop app" as the application type
- Download the JSON file
- Save the downloaded file as
client_secret.jsonin the project root
4. Configure Claude Desktop
Add the server to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"GoogleCalendar": {
"command": "uv",
"args": [
"--directory",
"/path/to/google-calendar-mcp-server-tutorial",
"run",
"main.py"
]
}
}
}
Replace /path/to/google-calendar-mcp-server-tutorial with the actual path to your project directory.
On first run, a browser window will open for Google OAuth authentication. After authentication, a token.json file will be created to store your credentials.
Available Tools
The server exposes the following MCP tools:
Calendar Tools
| Tool | Description |
|---|---|
list_calendars |
List all calendars in the user's calendar list |
get_calendar |
Get metadata for a specific calendar |
Event Tools
| Tool | Description |
|---|---|
list_events |
List events from a calendar with optional filters |
get_event |
Get details of a specific event |
create_event |
Create a new calendar event |
update_event |
Update an existing event |
delete_event |
Delete an event from a calendar |
Architecture
The project follows a layered architecture:
MCP Client (Claude Desktop)
↓
MCP Server (main.py + FastMCP)
↓
Tools (tools/) ←── Models (models/)
↓
Services (services/)
↓
Google Calendar API
- Tools - Define MCP tools that Claude can call, using Pydantic models for input validation
- Services - Handle business logic and Google Calendar API communication
- Service Factory - Dependency injection for creating and caching service instances
Configuration
Configuration is managed through config.py:
| Setting | Default | Description |
|---|---|---|
client_secret_path |
./client_secret.json |
Path to OAuth client secrets |
token_path |
./token.json |
Path to stored OAuth token |
log_file_path |
./server.log |
Path to log file |
log_level |
DEBUG |
Logging level (configurable via LOG_LEVEL env var) |
Tech Stack
- FastMCP - MCP server framework
- Google API Python Client - Google Calendar API integration
- google-auth-oauthlib - OAuth 2.0 authentication
- Pydantic - Data validation and settings management
- uv - Fast Python package manager
License
This project is for educational purposes.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。