cal2prompt MCP Server: Google Calendar Integration and Custom Prompt Generation

Overview: What is cal2prompt MCP Server?

cal2prompt is an innovative command-line tool designed to fetch schedules from Google Calendar and convert them into custom prompts or text snippets using a template engine. It can run as both a CLI application and an experimental MCP (Model Context Protocol) server, providing a versatile solution for integrating AI applications with specific data sources. The cal2prompt MCP Server leverages the robust features of the Rust ecosystem to ensure high-speed processing and flexibility in prompt customization. This document provides comprehensive documentation on setting up and utilizing cal2prompt as an MCP server.

🔧 Core Features & MCP Capabilities

cal2prompt offers a range of powerful features, including Google Calendar integration, flexible custom prompt generation using Jinja2 template engine, and experimental support for running as an MCP server. These capabilities enable seamless communication between AI applications like Claude Desktop, Continue, and Cursor through the standardized Model Context Protocol (MCP).

1. Google Calendar Integration

cal2prompt fetches events from your Google Calendar by utilizing the Google API v3. This ensures that you can leverage detailed scheduling information to tailor prompts specifically for the tasks at hand.

2. Flexible Custom Prompt Generation with Jinja2 Template Engine

With cal2prompt, users have full control over how their schedule is presented through customizable templates written in Jinja2. This feature allows for dynamic and context-aware prompt generation, enhancing AI application workflows by providing relevant information when needed.

3. Experimental Support for Running as an MCP Server

For developers looking to integrate cal2prompt with existing or new AI tools, the experimental MCP support provides a bridge between these applications and Google Calendar data. By running as an MCP server, users can fetch schedule-driven prompts and events, allowing for more personalized and context-aware interactions.

⚙️ MCP Architecture & Protocol Implementation

The cal2prompt MCP Server is designed with the Model Context Protocol in mind, ensuring compatibility with a range of AI tools through standardized communication protocols. The core architecture of the server includes:

1. Authentication and Authorization

cal2prompt authenticates users via OAuth 2.0 to fetch data from Google Calendar securely. This process involves generating temporary tokens that are stored locally for subsequent use.

2. Data Fetching & Processing

Once authenticated, cal2prompt retrieves events based on user-specified time ranges or predefined intervals (e.g., today, this week). These events are then processed and formatted using the Jinja2 template engine according to the user’s configuration.

3. MCP Protocol Flow and Data Handling

The MCP protocol is implemented by ensuring that requests from AI applications result in appropriate responses containing necessary schedule data. This data can be used directly by AI tools for generating prompts, planning tasks, or other context-aware interactions.

🚀 Getting Started with Installation

1. Brew (MacOS)

brew install shuntaka9576/tap/cal2prompt

2. Cargo (git)

git clone https://github.com/shuntaka9576/cal2prompt
cd cal2prompt
cargo install --path .

💡 Key Use Cases in AI Workflows

1. Personal Assistant Integration: Integrate cal2prompt with Claude Desktop or Continue to receive context-aware task prompts based on your calendar schedule.

2. Project Management Tool Enhancement: Use the generated prompts from cal2prompt within tools like Slack, Notion, or Trello for more organized project planning and execution.

🔌 Integration with MCP Clients

1. MCP Protocol Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

2. MCP Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

📊 Performance & Compatibility Matrix

cal2prompt is designed to handle a wide range of use cases with ease. The following table outlines the performance and compatibility matrix for various AI applications:

Feature	Claude Desktop	Continue	Cursor
Prompt Generation Speed	High	High	Medium
Calendar API Integration	✔	✔	✔
Template Engine Support	Full	Partial	Limited

🛠️ Advanced Configuration & Security

1. Initial Setup

Step 1: Set Up Google OAuth2.0 Client

cal2prompt

Follow the on-screen instructions to set up your own OAuth2.0 client and generate necessary tokens.

Step 2: Define User-Customizable Parameters

After setting up, define parameters such as time ranges, calendar IDs, and Jinja2 templates in config.lua or .env.

2. MCP Configuration Sample

{
  "mcpServers": {
    "cal2prompt": {
      "command": "cal2prompt",
      "args": ["--token-file=token.json"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. Q: Can cal2prompt be used with multiple calendar accounts?

   • A: Yes, multiple calendars can be specified in the configuration file to combine events from different sources.

2. Q: How do I ensure secure authentication for my Google Calendar data?

   • A: Use OAuth 2.0 tokens and store them securely using environment variables or encrypted files.

3. Q: What happens if my AI application is not compatible with MCP protocol currently?

   • A: Ensure that the AI application you are working with supports the Model Context Protocol by checking their compatibility matrix.

4. Q: Is there a way to customize the performance of cal2prompt for specific use cases?

   • A: Yes, advanced configurations allow tuning parameters like event parsing and template rendering speed.

5. Q: Can I run multiple instances of cal2prompt simultaneously?

   • A: While not recommended due to potential resource conflicts, you can run multiple instances by specifying different authentication tokens or configurations.

👨‍💻 Development & Contribution Guidelines

To contribute to the development of cal2prompt as an MCP server:

1. Clone the Repository:

   git clone https://github.com/shuntaka9576/cal2prompt.git
   

2. Set Up Environment:

   • Ensure Rust and Cargo are installed.
   • Run cargo build followed by cargo test.

3. Contribute Code: Open an issue or pull request on GitHub.

🌐 MCP Ecosystem & Resources

Explore the broader MCP ecosystem with other compatible tools and resources:

Tool / Resource	Description
ModelContextProtocol.org	Official documentation for the MCP protocol.
JetBrains AI Integration	Integrating AI tools with JetBrains IDEs using MCP.
OpenAI API Docs	Comprehensive guide to API integrations with various AI applications.

By following this comprehensive guide, developers can successfully integrate cal2prompt as an MCP server into their AI workflows, enhancing productivity and context-awareness for both personal and professional tasks.