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Google Drive & Sheets

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isaacphi

Model Context Protocol (MCP) Server for reading from Google Drive and editing Google Sheets

Publisherisaacphi
Repositorymcp-gdrive
LanguageTypeScript
Forks
102
Stars
275
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Google Drive & Sheets exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    275 stars and 102 forks from the linked repository.

Google Drive server

This MCP server integrates with Google Drive to allow listing, reading, and searching files, as well as the ability to read and write to Google Sheets.

This project includes code originally developed by Anthropic, PBC, licensed under the MIT License from this repo.

Components

Tools

  • gdrive_search

    • Description: Search for files in Google Drive.
    • Input:
      • query (string): Search query.
      • pageToken (string, optional): Token for the next page of results.
      • pageSize (number, optional): Number of results per page (max 100).
    • Output: Returns file names and MIME types of matching files.
  • gdrive_read_file

    • Description: Read contents of a file from Google Drive.
    • Input:
      • fileId (string): ID of the file to read.
    • Output: Returns the contents of the specified file.
  • gsheets_read

    • Description: Read data from a Google Spreadsheet with flexible options for ranges and formatting.
    • Input:
      • spreadsheetId (string): The ID of the spreadsheet to read.
      • ranges (array of strings, optional): Optional array of A1 notation ranges (e.g., ['Sheet1!A1:B10']). If not provided, reads the entire sheet.
      • sheetId (number, optional): Specific sheet ID to read. If not provided with ranges, reads the first sheet.
    • Output: Returns the specified data from the spreadsheet.
  • gsheets_update_cell

    • Description: Update a cell value in a Google Spreadsheet.
    • Input:
      • fileId (string): ID of the spreadsheet.
      • range (string): Cell range in A1 notation (e.g., 'Sheet1!A1').
      • value (string): New cell value.
    • Output: Confirms the updated value in the specified cell.

Resources

The server provides access to Google Drive files:

  • Files (gdrive:///<file_id>)
    • Supports all file types
    • Google Workspace files are automatically exported:
      • Docs → Markdown
      • Sheets → CSV
      • Presentations → Plain text
      • Drawings → PNG
    • Other files are provided in their native format

Getting started

  1. Create a new Google Cloud project
  2. Enable the Google Drive API
  3. Configure an OAuth consent screen ("internal" is fine for testing)
  4. Add OAuth scopes https://www.googleapis.com/auth/drive.readonly, https://www.googleapis.com/auth/spreadsheets
  5. In order to allow interaction with sheets and docs you will also need to enable the Google Sheets API and Google Docs API in your workspaces Enabled API and Services section.
  6. Create an OAuth Client ID for application type "Desktop App"
  7. Download the JSON file of your client's OAuth keys
  8. Rename the key file to gcp-oauth.keys.json and place into the path you specify with GDRIVE_CREDS_DIR (i.e. /Users/username/.config/mcp-gdrive)
  9. Note your OAuth Client ID and Client Secret. They must be provided as environment variables along with your configuration directory.
  10. You will also need to setup a .env file within the project with the following fields. You can find the Client ID and Client Secret in the Credentials section of the Google Cloud Console.
GDRIVE_CREDS_DIR=/path/to/config/directory
CLIENT_ID=<CLIENT_ID>
CLIENT_SECRET=<CLIENT_SECRET>

Make sure to build the server with either npm run build or npm run watch.

Authentication

Next you will need to run node ./dist/index.js to trigger the authentication step

You will be prompted to authenticate with your browser. You must authenticate with an account in the same organization as your Google Cloud project.

Your OAuth token is saved in the directory specified by the GDRIVE_CREDS_DIR environment variable.

Authentication Prompt

Usage with Desktop App

To integrate this server with the desktop app, add the following to your app's server configuration:

json
{
  "mcpServers": {
    "gdrive": {
      "command": "npx",
      "args": ["-y", "@isaacphi/mcp-gdrive"],
      "env": {
        "CLIENT_ID": "<CLIENT_ID>",
        "CLIENT_SECRET": "<CLIENT_SECRET>",
        "GDRIVE_CREDS_DIR": "/path/to/config/directory"
      }
    }
  }
}

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "gdrive": {
      "command": "npx",
      "args": [
        "-y",
        "@isaacphi/mcp-gdrive"
      ],
      "env": {
        "CLIENT_ID": "<CLIENT_ID>",
        "CLIENT_SECRET": "<CLIENT_SECRET>",
        "GDRIVE_CREDS_DIR": "/path/to/config/directory"
      }
    }
  }
}

Use Google Drive & Sheets MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Google Drive & Sheets is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Google Drive & Sheets as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Google Drive & Sheets MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "google-drive-sheets": {
      "command": "npx",
      "args": [
        "-y",
        "@isaacphi/mcp-gdrive"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Google Drive & Sheets MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Google Drive & Sheets MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Google Drive & Sheets to help me with this task?
Google Drive & Sheets
Sure. I read it.
Here is what I found using Google Drive & Sheets.

Frequently asked questions

What is the Google Drive & Sheets MCP server used for?

Google Drive & Sheets is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Google Drive & Sheets MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Google Drive & Sheets with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Google Drive & Sheets MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Google Drive & Sheets connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Google Drive & Sheets MCP to TypingMind?

Google Drive & Sheets runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Google Drive & Sheets MCP provide in TypingMind?

Google Drive & Sheets exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Google Drive & Sheets MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Google Drive & Sheets requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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