MCP Calendar Tool Server
@KyanBergeron4Runr
About MCP Calendar Tool Server
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Basic information
Config
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Overview
What is MCP Calendar Tool Server?
A FastAPI-based MCP (Model Context Protocol) server that provides calendar management tools—check availability, add, update, and delete events—for AI agents running in n8n.
How to use MCP Calendar Tool Server?
Clone the repository, install dependencies with pip install -r requirements.txt, create a .env file with your API key, then run uvicorn main:app --host 0.0.0.0 --port 5000. Connect n8n’s MCP Client node to the SSE endpoint at http://localhost:8000/mcp-events.
Key features of MCP Calendar Tool Server
- Server-Sent Events (SSE) for real-time tool discovery
- HTTP endpoints for tool execution
- Four calendar management tools: check availability, add, update, delete
- API key authentication
- Mock implementations ready for real calendar API integration
- Structured project with Pydantic schemas and separate tool modules
Use cases of MCP Calendar Tool Server
- AI agents in n8n that need to check room availability before scheduling meetings
- Automating event creation from chatbot conversations or workflow triggers
- Updating or rescheduling calendar events without manual intervention
- Deleting cancelled events through automated n8n workflows
FAQ from MCP Calendar Tool Server
What dependencies are required?
Python packages listed in requirements.txt; install with pip install -r requirements.txt.
How is authentication handled?
The server uses an API key set in the .env file as API_KEY. All tool execution requests require the X-API-Key header.
Does it integrate with real calendar services?
No, the current version uses mock implementations. Future improvements include integration with Google Calendar, Cal.com, and others.
What transport does the server use?
It uses Server-Sent Events (SSE) for tool discovery (GET /mcp-events) and HTTP POST for tool execution (POST /mcp/message).
What are the current limitations?
The server provides mock data only, no real calendar backend. It requires Python 3 and a running FastAPI instance.
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