Calendly MCP Server Integration

What does “Calendly” MCP Server do?

The Calendly MCP (Model Context Protocol) Server acts as a bridge between AI assistants and Calendly’s scheduling tools and services. By exposing a standardized MCP interface, it allows AI agents and developers to programmatically interact with Calendly functionalities—such as viewing, creating, or managing events—via a unified API. This integration is designed to enhance developer workflows by enabling automated scheduling, appointment management, and seamless access to calendar data directly from within AI-driven applications. Built on the Universal MCP framework, the server follows the MCP specification, ensuring compatibility and interoperability with other MCP-compliant tools and services. Its main purpose is to streamline the way AI systems leverage external scheduling capabilities, making it easier to coordinate meetings and manage calendars efficiently.

List of Prompts

No prompt templates are mentioned in the repository.

List of Resources

No resources are detailed or exposed in the repository.

List of Tools

The repository references a list of available tools in src/universal_mcp_calendly/README.md, but the specific tools are not listed or described in the root README or visible file-tree.

Use Cases of this MCP Server

• Automated Scheduling: Integrate with AI agents to automatically schedule meetings based on user or team availability, reducing manual coordination.
• Appointment Management: Enable AI assistants to view, create, update, or cancel appointments in Calendly, streamlining workflow automation for businesses and individuals.
• Calendar Synchronization: Facilitate syncing of events and meetings between Calendly and other calendar platforms to maintain up-to-date schedules.
• Smart Reminders and Notifications: Allow AI systems to send reminders or notifications for upcoming events, minimizing missed appointments.
• Workflow Integration: Connect Calendly scheduling with broader business logic, such as CRM or project management tools, via AI-driven triggers and actions.

How to set it up

Windsurf

1. Ensure you have Node.js and Windsurf installed.
2. Open your Windsurf configuration file.
3. Add the Calendly MCP Server to your mcpServers object:

   {
     "mcpServers": {
       "calendly": {
         "command": "npx",
         "args": ["@universal-mcp/calendly@latest"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the Calendly MCP Server is running.

Securing API Keys:

{
  "mcpServers": {
    "calendly": {
      "command": "npx",
      "args": ["@universal-mcp/calendly@latest"],
      "env": {
        "CALENDLY_API_KEY": "${CALENDLY_API_KEY}"
      },
      "inputs": {
        "api_key": "${CALENDLY_API_KEY}"
      }
    }
  }
}

Claude

1. Ensure Claude is installed and configured.
2. Open the Claude configuration file.
3. Add the Calendly MCP Server:

   {
     "mcpServers": {
       "calendly": {
         "command": "npx",
         "args": ["@universal-mcp/calendly@latest"]
       }
     }
   }
   

4. Save, restart Claude, and verify the server is available.

Securing API Keys:

{
  "mcpServers": {
    "calendly": {
      "command": "npx",
      "args": ["@universal-mcp/calendly@latest"],
      "env": {
        "CALENDLY_API_KEY": "${CALENDLY_API_KEY}"
      },
      "inputs": {
        "api_key": "${CALENDLY_API_KEY}"
      }
    }
  }
}

Cursor

1. Install Node.js and Cursor.
2. Open Cursor’s configuration file.
3. Add the Calendly MCP Server to the configuration:

   {
     "mcpServers": {
       "calendly": {
         "command": "npx",
         "args": ["@universal-mcp/calendly@latest"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Confirm Calendly MCP Server is active.

Securing API Keys:

{
  "mcpServers": {
    "calendly": {
      "command": "npx",
      "args": ["@universal-mcp/calendly@latest"],
      "env": {
        "CALENDLY_API_KEY": "${CALENDLY_API_KEY}"
      },
      "inputs": {
        "api_key": "${CALENDLY_API_KEY}"
      }
    }
  }
}

Cline

1. Make sure Cline and Node.js are installed.
2. Edit Cline’s configuration file.
3. Insert the Calendly MCP Server config:

   {
     "mcpServers": {
       "calendly": {
         "command": "npx",
         "args": ["@universal-mcp/calendly@latest"]
       }
     }
   }
   

4. Save, restart Cline, and check the server status.

Securing API Keys:

{
  "mcpServers": {
    "calendly": {
      "command": "npx",
      "args": ["@universal-mcp/calendly@latest"],
      "env": {
        "CALENDLY_API_KEY": "${CALENDLY_API_KEY}"
      },
      "inputs": {
        "api_key": "${CALENDLY_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "calendly": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “calendly” to whatever the actual name of your MCP server is (e.g., “github-mcp”, “weather-api”, etc.) and replace the URL with your own MCP server URL.

Overview

Based on the available documentation and the information in the repository, this MCP is at an early stage. It provides basic setup and security instructions but lacks public details on supported tools, resources, prompts, and advanced MCP features like Roots or Sampling.

Our opinion

This MCP server provides a minimal but official scaffold for Calendly integration via MCP, with clear instructions and licensing. However, due to the lack of detailed technical documentation and missing lists of tools, prompts, and resources, its practical utility is currently limited for developers seeking out-of-the-box functionality.

Rating: 3/10

MCP Score