Calendar MCP Server

The Calendar MCP Server bridges the gap between AI assistants and Google Calendar, enabling assistants such as Claude to retrieve event lists directly from a user’s calendar. By exposing the Google Calendar API through the Model Context Protocol, developers can embed up-to-date scheduling information into conversational flows without handling OAuth intricacies themselves. This is especially valuable in contexts where time management or event coordination is central—meeting planners, travel assistants, or productivity bots can now ask the AI to “show me my upcoming meetings” and receive a precise, authenticated response.

At its core, the server authenticates with Google using OAuth 2.0 for installed applications. After a user authorizes the application once, the server caches the credentials and can subsequently query the Calendar API to list events within a specified window. The MCP interface exposes this functionality as a simple tool or resource that the AI can invoke with minimal input: for example, a prompt like “List my events for tomorrow” triggers the server to fetch and return that data. Because the server handles token refreshes internally, developers need not worry about session management or re‑authenticating during long conversations.

Key capabilities include:

• Event retrieval: Fetches a user’s scheduled events for any given date range or time slot.
• Real‑time updates: Supports immediate reflection of new or modified events, ensuring the assistant’s responses are always current.
• Secure OAuth flow: Uses a locally hosted callback endpoint () to complete the authorization process, keeping credentials out of client code.
• Simple MCP integration: Exposes a single resource that can be referenced in prompts, making it straightforward to incorporate into existing MCP workflows.

Typical use cases span a wide spectrum: a virtual secretary can generate daily agendas, a travel planner can suggest itineraries based on calendar availability, and team collaboration tools can surface upcoming meetings during project discussions. In each scenario, the AI gains access to authoritative scheduling data without requiring users to manually input dates or times.

Integrating this server into an AI workflow is seamless. Once the MCP server is running, developers add its reference to their , allowing the assistant to call the calendar resource on demand. The server’s response is returned in a structured format that can be parsed or displayed directly, enabling rich conversational experiences. The design prioritizes security, minimal friction, and real‑time accuracy—making the Calendar MCP Server a standout solution for developers who need reliable calendar integration in their AI-powered applications.