Google Workspace MCP Server

What does “Google Workspace” MCP Server do?

The Google Workspace MCP Server is a comprehensive, highly performant Model Context Protocol (MCP) server designed to seamlessly connect AI assistants and large language models with various Google Workspace services. By providing complete coverage for Calendar, Gmail, Docs, Sheets, Slides, Chat, Forms, and Drive, this MCP server empowers developers to create workflows that can access, modify, and interact with Google Workspace data programmatically. It enables tasks such as querying calendar events, managing emails, handling documents, collaborating on sheets, and integrating with chat and forms, all through standardized MCP tools and resources. This greatly enhances the productivity and automation capabilities of AI-driven applications within organizations that rely on Google Workspace.

List of Prompts

No prompt templates are explicitly mentioned in the repository files or documentation.

List of Resources

No explicit list of MCP resources is detailed in the available repository content.

List of Tools

Based on the folder structure and coverage description, the following tools are likely provided by the Google Workspace MCP Server, each corresponding to a Google Workspace product:

• gcalendar: Tools to manage and query Google Calendar events, schedules, and reminders.
• gmail: Tools for sending, reading, and organizing emails.
• gdocs: Tools to create, edit, and retrieve Google Docs documents.
• gsheets: Tools for interacting with spreadsheets, including reading and writing data.
• gslides: Tools to manage Google Slides presentations.
• gchat: Tools for accessing and sending messages in Google Chat.
• gforms: Tools for interacting with Google Forms, such as retrieving responses or managing forms.
• gdrive: Tools to access, upload, download, and organize files in Google Drive.

Use Cases of this MCP Server

• Automated Meeting Scheduling: Integrate with Google Calendar to find available time slots and schedule meetings directly from an AI assistant.
• Email Management: Use AI to automatically sort, respond to, or summarize Gmail messages, reducing manual inbox management.
• Collaborative Document Editing: Enable AI-powered suggestions or real-time editing of Docs, Sheets, or Slides for team projects.
• Data Extraction and Reporting: Automate reading, analyzing, and reporting from Sheets or Forms data for business intelligence tasks.
• Unified Workspace Automation: Seamlessly automate workflows that span multiple Google Workspace services, such as creating a meeting, sending invites, and generating a follow-up document.

How to set it up

Windsurf

1. Ensure you have Node.js and npm/yarn installed.
2. Open your Windsurf configuration file (e.g., windsurf.config.json).
3. Add the Google Workspace MCP Server under mcpServers:

   {
     "mcpServers": {
       "google-workspace": {
         "command": "npx",
         "args": ["@google-workspace/mcp-server@latest"]
       }
     }
   }
   

4. Save the file and restart Windsurf.
5. Verify the server connection in the Windsurf UI.

Example with environment variables:

{
  "mcpServers": {
    "google-workspace": {
      "command": "npx",
      "args": ["@google-workspace/mcp-server@latest"],
      "env": {
        "GOOGLE_API_KEY": "${GOOGLE_API_KEY}"
      },
      "inputs": {}
    }
  }
}

Claude

1. Install Node.js if not already present.
2. Locate Claude’s MCP configuration file.
3. Add the Google Workspace MCP Server entry:

   {
     "mcpServers": {
       "google-workspace": {
         "command": "npx",
         "args": ["@google-workspace/mcp-server@latest"]
       }
     }
   }
   

4. Save configuration and restart Claude.
5. Confirm the server is running by checking Claude’s interface.

Example with environment variables:

{
  "mcpServers": {
    "google-workspace": {
      "command": "npx",
      "args": ["@google-workspace/mcp-server@latest"],
      "env": {
        "GOOGLE_API_KEY": "${GOOGLE_API_KEY}"
      },
      "inputs": {}
    }
  }
}

Cursor

1. Prerequisite: Install Node.js.
2. Edit Cursor’s MCP configuration file.
3. Add the following under mcpServers:

   {
     "mcpServers": {
       "google-workspace": {
         "command": "npx",
         "args": ["@google-workspace/mcp-server@latest"]
       }
     }
   }
   

4. Save changes and relaunch Cursor.
5. Verify integration in the Cursor UI.

Example with environment variables:

{
  "mcpServers": {
    "google-workspace": {
      "command": "npx",
      "args": ["@google-workspace/mcp-server@latest"],
      "env": {
        "GOOGLE_API_KEY": "${GOOGLE_API_KEY}"
      },
      "inputs": {}
    }
  }
}

Cline

1. Install Node.js if not already installed.
2. Open (or create) the Cline MCP configuration file.
3. Insert the Google Workspace MCP Server configuration:

   {
     "mcpServers": {
       "google-workspace": {
         "command": "npx",
         "args": ["@google-workspace/mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Confirm that the server is working in the Cline dashboard.

Example with environment variables:

{
  "mcpServers": {
    "google-workspace": {
      "command": "npx",
      "args": ["@google-workspace/mcp-server@latest"],
      "env": {
        "GOOGLE_API_KEY": "${GOOGLE_API_KEY}"
      },
      "inputs": {}
    }
  }
}

Note: Secure your API keys by using environment variables as shown above. Never hardcode sensitive credentials in configuration files.

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:

{
  "google-workspace": {
    "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 “google-workspace” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the information available, the Google Workspace MCP Server offers strong integration and tool coverage but lacks publicly documented prompts, resources, or sampling/roots support. The setup instructions are standard, and API security is addressed. Overall, this MCP scores highly for functionality and potential, though some documentation areas could be improved.

MCP Score