MCP Servers

Reminders MCP Server

Enables interaction with macOS Reminders app through AppleScript, allowing users to create, read, update, and delete reminders and lists, with support for filtering, batch operations, and reminder properties like priority and due dates.

README

Reminders MCP Server

An MCP (Model Context Protocol) server for interacting with macOS Reminders app via AppleScript.

Requirements

macOS
Node.js >= 18.0.0
Access to macOS Reminders app

Installation

npm install -g reminders-mcp

Or use directly with npx:

npx reminders-mcp

Usage

As an MCP Server

Add to your MCP client configuration:

{
  "mcpServers": {
    "reminders": {
      "command": "npx",
      "args": ["reminders-mcp"]
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "reminders": {
      "command": "reminders-mcp"
    }
  }
}

Development

git clone https://github.com/jagadeesh52423/remainders-mcp.git
cd remainders-mcp
npm install
npm run dev        # Run with tsx
npm run inspector  # Run with MCP inspector

Available Tools

Lists

Tool	Description
`list_reminder_lists`	Get all reminder lists with names, IDs, and counts
`create_reminder_list`	Create a new reminder list
`delete_reminder_list`	Delete a list and all its reminders
`rename_reminder_list`	Rename an existing list

Reminders

Tool	Description
`get_reminders`	Get reminders with filtering (list, status, priority, date range, search)
`get_reminder`	Get a single reminder by ID
`create_reminder`	Create a new reminder
`update_reminder`	Update reminder properties
`delete_reminder`	Delete a reminder
`complete_reminder`	Mark reminder as completed/incomplete

Batch Operations

Tool	Description
`batch_create_reminders`	Create multiple reminders at once (max 100)
`batch_update_reminders`	Update multiple reminders at once (max 100)
`batch_complete_reminders`	Complete/uncomplete multiple reminders (max 100)

License

MIT

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official

Featured

TypeScript

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official

Featured

Local

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official

Featured

Python

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official

Featured

TypeScript

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official

Featured

Neon Database

MCP server for interacting with Neon Management API and databases

Official

Featured

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official

Featured

E2B

Using MCP to run code via e2b.

Official

Featured