google-workspace-mcp-server
Enables AI agents to send Gmail messages and append content to Google Docs using the Model Context Protocol.
README
Google Workspace MCP Server
A generic, agent-agnostic MCP (Model Context Protocol) server that exposes Gmail and Google Docs as tools any AI agent can call.
| Tool | Description |
|---|---|
gmail_send_email |
Send or draft emails via Gmail |
google_docs_append |
Append plain text or markdown to a Google Doc |
Built with FastMCP — any MCP-compatible client (Claude Desktop, Cursor, custom agents) can discover and invoke these tools automatically..
Prerequisites
- Python 3.10+
- Google Cloud project with Gmail API and Google Docs API enabled
- OAuth 2.0 Client ID (Desktop application type)
Google Cloud Setup
If you don't have a Google Cloud project yet, follow these steps:
- Go to Google Cloud Console
- Create a new project (or select an existing one)
- Enable APIs:
- Navigate to APIs & Services → Library
- Search for and enable Gmail API
- Search for and enable Google Docs API
- Create OAuth Credentials:
- Go to APIs & Services → Credentials
- Click Create Credentials → OAuth 2.0 Client ID
- Application type: Desktop app
- Download the JSON file and save it as
credentials.jsonin the project root
- Configure OAuth Consent Screen:
- Go to APIs & Services → OAuth consent screen
- Choose External (or Internal for Workspace)
- Add your email as a test user
- Add scopes:
https://www.googleapis.com/auth/gmail.sendhttps://www.googleapis.com/auth/gmail.composehttps://www.googleapis.com/auth/documents
Installation
# Clone the repository
git clone <your-repo-url>
cd "MCP Server"
# Create and activate a virtual environment
python -m venv venv
venv\Scripts\activate # Windows
# source venv/bin/activate # macOS/Linux
# Install dependencies
pip install -r requirements.txt
Configuration
Copy the example environment file and adjust if needed:
cp .env.example .env
| Variable | Default | Description |
|---|---|---|
GOOGLE_CREDENTIALS_PATH |
./credentials.json |
Path to OAuth client ID JSON |
GOOGLE_TOKEN_PATH |
./token.json |
Path where the auth token is saved |
First Run & Authentication
python server.py
On the first run, your browser will open for Google OAuth consent. Grant the requested permissions. A token.json file will be created automatically — subsequent runs will use this token (and refresh it when expired).
Note: When using stdio transport, the server communicates via stdin/stdout. The OAuth browser flow happens once; after that, the server runs headless.
Connecting to AI Agents
Claude Desktop
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"google-workspace": {
"command": "python",
"args": ["C:/full/path/to/MCP Server/server.py"]
}
}
}
Restart Claude Desktop — the tools will appear in the tool picker.
Cursor
Add to your Cursor MCP config (.cursor/mcp.json):
{
"mcpServers": {
"google-workspace": {
"command": "python",
"args": ["C:/full/path/to/MCP Server/server.py"]
}
}
}
MCP Inspector (Testing)
mcp dev server.py
This opens a web UI where you can test both tools interactively.
Tool Reference
gmail_send_email
Send an email or save it as a draft.
Parameters:
| Name | Type | Required | Description |
|---|---|---|---|
to |
list[str] |
✅ | Recipient email addresses |
subject |
str |
✅ | Email subject line |
body |
str |
✅ | Email body (plain text or HTML) |
cc |
list[str] |
❌ | CC recipients |
bcc |
list[str] |
❌ | BCC recipients |
is_draft |
bool |
❌ | Save as draft instead of sending (default: false) |
Example response:
{
"status": "sent",
"message_id": "18a1b2c3d4e5f6g7",
"thread_id": "18a1b2c3d4e5f6g7"
}
google_docs_append
Append content to an existing Google Doc.
Parameters:
| Name | Type | Required | Description |
|---|---|---|---|
document_id |
str |
✅ | Google Doc ID (from URL) |
content |
str |
✅ | Text to append |
format |
str |
❌ | "plain" (default) or "markdown" |
Example response:
{
"status": "appended",
"document_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUii3Op3Rp6mLbKd",
"characters_added": 142
}
Markdown support: When format="markdown", the tool converts:
# Heading→ Google Docs Heading 1–6**bold**→ Bold text*italic*→ Italic text
Development
Running Unit Tests
# All unit tests (no credentials needed)
pytest tests/test_gmail_tool.py tests/test_docs_tool.py -v
Running Integration Tests
Requires real credentials and environment variables:
# Set test targets
set TEST_DOCUMENT_ID=your-google-doc-id
set TEST_EMAIL_RECIPIENT=your-email@example.com
# Run integration tests
pytest tests/test_integration.py -v -m integration
Adding a New Tool
- Create a new module in
tools/(e.g.,tools/sheets_tool.py) - Add any new scopes to
config/scopes.py - Register the tool in
server.pywith@mcp.tool() - Add unit tests in
tests/ - Re-run
python server.pyor restart your MCP client
Deploy to Railway
This server can be deployed to Railway for remote access via SSE transport.
Step 1: Push to GitHub
git init
git add .
git commit -m "Initial commit: MCP server for Gmail & Google Docs"
git remote add origin https://github.com/<YOUR_USERNAME>/<REPO_NAME>.git
git branch -M main
git push -u origin main
Step 2: Create Railway Project
- Go to railway.app → sign in
- New Project → Deploy from GitHub Repo → select your repo
- Railway will auto-detect the
Procfileand start deploying
Step 3: Set Environment Variables
In Railway dashboard → your service → Variables tab:
| Variable | Value |
|---|---|
GOOGLE_TOKEN_JSON |
Paste the entire contents of your local token.json |
MCP_TRANSPORT |
sse |
Note: Railway automatically sets
PORT. The server detects this and switches to SSE transport.
Step 4: Connect Your Agent
After deploy, Railway provides a public URL. Your SSE endpoint is:
https://your-app.railway.app/sse
Claude Desktop (remote SSE):
{
"mcpServers": {
"google-workspace": {
"url": "https://your-app.railway.app/sse"
}
}
}
Project Structure
MCP Server/
├── server.py # MCP server entry point (FastMCP)
├── Procfile # Railway process definition
├── runtime.txt # Python version for Railway
├── tools/
│ ├── gmail_tool.py # Gmail send/draft logic
│ └── google_docs_tool.py # Google Docs append logic
├── auth/
│ └── google_auth.py # Shared OAuth 2.0 auth helper
├── config/
│ └── scopes.py # Centralised Google API scopes
├── tests/
│ ├── test_gmail_tool.py # Gmail unit tests
│ ├── test_docs_tool.py # Docs unit tests
│ └── test_integration.py # End-to-end integration tests
├── generate_token.py # OAuth token generator utility
├── credentials.json # OAuth client ID (gitignored)
├── token.json # Auto-generated token (gitignored)
├── requirements.txt
├── .env.example
├── .gitignore
└── README.md
Security
- credentials.json and token.json are gitignored — never commit them.
- For deployment, credentials are loaded from environment variables — no secrets in code.
- The server uses least-privilege scopes (send/compose for Gmail, documents for Docs).
- AI agents never see or handle Google credentials — the MCP server manages auth internally.
- No PII is logged.
License
MIT
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