Google Calendar MCP Server
@agc129
关于 Google Calendar MCP Server
暂无概览
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"gcal-mcp-server": {
"command": "uv",
"args": [
"venv"
]
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Google Calendar MCP Server?
Google Calendar MCP Server is a Model Context Protocol (MCP) server that provides integration with Google Calendar. It allows LLM applications to manage calendar events through a standardized interface.
How to use Google Calendar MCP Server?
Set up a .env file with required environment variables, then run uv run client.py after installing the package in a virtual environment. The server exposes tools for listing, creating, updating, and deleting calendar events.
Key features of Google Calendar MCP Server
- List available calendars
- List events from a calendar
- Create new calendar events
- Update existing events
- Delete events
Use cases of Google Calendar MCP Server
- An LLM assistant helping a user view upcoming events
- Automatically scheduling meetings based on natural language requests
- Modifying or deleting events as part of a workflow
- Integrating calendar management into a chatbot or AI agent
FAQ from Google Calendar MCP Server
What Google Cloud setup is required?
You need a Google Cloud project with the Calendar API enabled and OAuth 2.0 credentials (Desktop app type). Add your email as a test user under the OAuth Consent screen.
How do I install the server?
Clone the repository, create a virtual environment with uv venv, activate it, and run uv pip install -e . to install the package in editable mode.
What transports or authentication does it use?
The README does not specify transport details. It uses OAuth 2.0 for authentication with Google Calendar API, with credentials obtained from Google Cloud Console.
Does it require any runtime dependencies?
Yes, it requires Python with uv and the Google Calendar API client libraries (installed via the editable install). A .env file with environment variables is also needed.
Can it be used with any LLM platform?
The README does not specify platform compatibility beyond being an MCP server. It is designed for LLM applications that support the Model Context Protocol.
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