Auralis Google

MCP server for Google Workspace integration with Claude AI

Auralis Google provides seamless integration between Claude AI and Google Workspace services through the Model Context Protocol (MCP). Access Gmail, Calendar, Drive, Docs, and Sheets directly from Claude.

Features

• Gmail: Search messages, read emails, send emails, manage labels

• Calendar: List events, create/update/delete events, list calendars

• Drive: List files, search, read content, create/delete files and folders

• Docs: Read documents, append text, create new docs

• Sheets: Full spreadsheet management - read, write, append, delete rows, manage sheets

Related MCP server: google-workspace-mcp-with-script

Installation

Option 1: npm (Recommended)

npm install -g auralis-google

Option 2: Docker

docker pull antonpme/auralis-google
docker run -p 3000:3000 \
  -e GOOGLE_CLIENT_ID=your_client_id \
  -e GOOGLE_CLIENT_SECRET=your_client_secret \
  -e GOOGLE_REDIRECT_URI=http://localhost:3000/oauth/callback \
  antonpme/auralis-google

Option 3: Clone and Build

git clone https://github.com/antonpme/auralis-google.git
cd auralis-google
npm install
npm run build

Google Cloud Setup

Before using Auralis Google, you need to create OAuth credentials:

1. Go to Google Cloud Console

2. Create a new project or select existing one

3. Enable the following APIs:

   • Gmail API

   • Google Calendar API

   • Google Drive API

   • Google Docs API

   • Google Sheets API

4. Go to Credentials → Create Credentials → OAuth client ID

5. Select Web application

6. Add authorized redirect URI: http://localhost:3000/oauth/callback

7. Copy Client ID and Client Secret

Configuration

Claude Desktop (stdio mode)

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "google": {
      "command": "auralis-google",
      "env": {
        "MCP_MODE": "stdio",
        "GOOGLE_CLIENT_ID": "your_client_id.apps.googleusercontent.com",
        "GOOGLE_CLIENT_SECRET": "your_client_secret",
        "GOOGLE_REDIRECT_URI": "http://localhost:3000/oauth/callback"
      }
    }
  }
}

HTTP Mode (Railway/Docker)

Set these environment variables:

HTTP Endpoints:

Authentication

On first use, you need to authenticate with Google:

HTTP Mode:

1. Open http://localhost:3000/auth?account=personal in browser

2. Sign in with your Google account

3. Grant permissions

4. You'll see "✅ Authenticated as your@email.com"

Stdio Mode: You'll need to run the server in HTTP mode first to complete OAuth, then switch to stdio.

Multiple Accounts

You can authenticate multiple Google accounts:

/auth?account=personal
/auth?account=work
/auth?account=client

Then specify the account when using tools:

{
  "account": "work",
  "query": "is:unread"
}

Tools Reference

Account Management

Gmail (4 tools)

Calendar (5 tools)

Drive (8 tools)

Docs (3 tools)

Sheets (10 tools)

Usage Examples

Search unread emails

Search my Gmail for unread messages from last week

Create calendar event

Create a meeting called "Project Review" tomorrow at 3pm for 1 hour

Read spreadsheet data

Read all data from my Budget spreadsheet

Send email

Send an email to john@example.com with subject "Meeting Notes" and the summary of our discussion

Comparison with Google Workspace CLI

Google released the Google Workspace CLI (gws) in March 2026 — a Rust-based CLI + MCP server that dynamically discovers all Google APIs. It's an impressive project. Here's how it compares:

At a Glance

Why Auralis Google

1. Remote-first architecture

Auralis Google runs on Railway, Docker, or any cloud provider. Your AI assistant accesses Google APIs from anywhere — not just your local machine. gws MCP mode only works over stdio (local process).

2. Production-stable

Real-world usage across multiple accounts. No auth loops, no token refresh issues, no scope conflicts. gws is under active development with open auth-related issues.

3. Right-sized tool surface

31 purpose-built tools that cover the core Google Workspace workflow. Your AI doesn't burn context tokens loading 200+ tool definitions. Each tool has clear input schemas with Zod validation.

4. Hackable

TypeScript source you can read, modify, and extend. Need a custom tool? Add it in 20 lines. Rust binaries don't offer that flexibility.

When to consider gws instead

• You need Google services beyond the core 5 (Slides, Forms, Tasks, Meet, Chat, Keep, Admin)

• You want CLI access to Google APIs (not just MCP)

• You prefer a single tool for everything and don't need remote deployment

• You're comfortable with pre-v1.0 software and can work through auth issues

Summary

Our take: Use Auralis Google for production AI workflows. Keep an eye on gws as it matures — it could become a great complement for services outside the core 5.

Railway Deployment

1. Fork this repository

2. Connect to Railway

3. Set environment variables in Railway dashboard

4. Deploy

Or use the railway.json included in this repo.

Architecture

auralis-google/
├── src/
│   ├── index.ts      # MCP server + Express endpoints
│   ├── auth.ts       # OAuth2 management
│   └── tools/
│       ├── gmail.ts
│       ├── calendar.ts
│       ├── drive.ts
│       ├── docs.ts
│       └── sheets.ts
├── dist/             # Compiled JavaScript
├── data/             # Token storage (gitignored)
├── Dockerfile
├── railway.json
└── package.json

Security

• OAuth tokens are stored locally in ./data/tokens.json

• Tokens are automatically refreshed when expired

• Never commit your data/ folder or .env files

• Use environment variables for credentials

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

MIT License - see LICENSE file.

Links

• GitHub Repository

• NPM Package

• Auralis Commander - Windows MCP server