Ai Scheduler MCP

The Ai Scheduler MCP is a lightweight Model Context Protocol server that bridges Google Tasks and Calendar APIs with AI assistants such as Claude or Roo Code. By exposing these calendar services through a standardized MCP interface, the server eliminates the need for developers to write custom OAuth flows or API wrappers. Instead, any MCP‑compliant client can query tasks, create events, update schedules, or delete items simply by sending structured requests over a Server‑Sent Events (SSE) stream. This integration is especially valuable for building conversational agents that need to read or modify a user’s schedule in real time.

What Problem Does It Solve?

Modern productivity workflows often rely on a single calendar or task list, but many users spread their commitments across multiple tools. Integrating Google’s Task and Calendar APIs directly into an AI assistant allows a single conversational interface to manage all time‑related information. Without this MCP server, developers would have to implement OAuth 2.0 authentication, token refresh logic, and individual API endpoints for each service—a repetitive and error‑prone process. The Ai Scheduler MCP encapsulates all of that complexity, providing a clean, secure entry point for AI workflows.

Core Capabilities

• Unified Calendar & Task Access: Create, read, update, and delete events or tasks in a single API call.
• OAuth 2.0 Handling: A one‑time authentication flow generates a secure that the server uses to access Google APIs on behalf of the user.
• SSE Communication: The server streams responses back to clients in real time, enabling responsive conversational experiences.
• Docker‑Ready: The entire stack runs inside a Docker container, ensuring consistent deployment across environments.
• Network Flexibility: Clients can connect via localhost or through a shared Docker network, making it easy to integrate with other containerized services.

Real‑World Use Cases

• Personal Assistant Bots: A chatbot can check the next meeting, add a reminder, or reschedule an event without leaving the conversation.
• Team Collaboration Tools: An AI helper can pull task lists for a project, suggest optimal meeting slots, and automatically create calendar invites.
• Automated Scheduling Scripts: Backend services can use the MCP to sync tasks with external systems, trigger notifications, or generate reports on calendar usage.
• Voice‑Activated Interfaces: Smart speakers or mobile assistants can query the server to confirm availability, set alarms, or update task statuses.

Integration Flow

1. Deploy the MCP Server in a Docker container, ensuring and are stored securely.
2. Configure the AI client (e.g., Roo Code) to point at the server’s SSE endpoint.
3. Send structured requests (e.g., “list upcoming events”) and receive immediate, parsed responses.
4. Handle results within the AI workflow—displaying them to users or triggering further actions.

Standout Advantages

• Zero API Boilerplate: All OAuth, token management, and SSE handling are pre‑built.
• Secure Credential Management: Sensitive files are ignored by Git and stored locally, reducing exposure risk.
• Scalable Deployment: Docker makes it trivial to run multiple instances or integrate with CI/CD pipelines.
• Extensible Architecture: The server’s design allows additional Google services or custom tools to be added with minimal effort.

By centralizing Google Tasks and Calendar interactions behind a single, protocol‑compliant interface, the Ai Scheduler MCP empowers developers to build richer, contextually aware AI assistants that can manage time and tasks seamlessly within conversational flows.