Google Docs & Gmail MCP Server

A complete Model Context Protocol (MCP)-style server in Python using FastAPI that integrates directly with Google Docs and Gmail via the official Google APIs with OAuth 2.0 authentication and interactive terminal-based human-in-the-loop approval.

📁 Project Structure

google-mcp-server/
├── server.py          → FastAPI app with tool endpoints & terminal confirmation
├── auth.py            → Google OAuth 2.0 authentication & token persistence
├── docs_tool.py       → Google Docs tool (appends content to docs)
├── gmail_tool.py      → Gmail tool (creates email drafts)
├── requirements.txt   → Python package dependencies
├── .gitignore         → Prevents committing credentials.json & token.json
├── Procfile           → Railway / PaaS process declaration
├── railway.toml       → Railway build & healthcheck configuration
├── Dockerfile         → Container definition for cloud deployments
├── deployment.md      → Detailed Railway cloud deployment guide
├── README.md          → Setup, configuration, and usage instructions
├── credentials.json   → (NOT committed — downloaded from Google Cloud Console)
└── token.json         → (NOT committed — auto-generated after first OAuth login)

Related MCP server: MCP Google Workspace Server

⚙️ Features

1. Google OAuth 2.0 Authentication (auth.py):

   • Scopes configured:

     • https://www.googleapis.com/auth/documents (Google Docs read/write)

     • https://www.googleapis.com/auth/gmail.compose (Gmail draft creation)

   • Automatically loads existing token.json without re-opening the browser.

   • Automatically refreshes expired tokens.

   • Automatically launches browser-based OAuth consent flow on initial run and writes token.json.

2. Google Docs Tool (docs_tool.py):

   • append_to_doc(doc_id: str, content: str)

   • Appends text content to the end of any Google Doc using the official Google Docs API v1 (documents.batchUpdate).

3. Gmail Tool (gmail_tool.py):

   • create_email_draft(to: str, subject: str, body: str)

   • Creates a new draft message in the authenticated user's Gmail using the official Gmail API v1 (users.drafts.create).

4. FastAPI Server with Human-in-the-loop Approval (server.py):

   • POST /append_to_doc: Appends text to a document.

   • POST /create_email_draft: Creates an email draft.

   • Terminal Gatekeeper: Before executing any tool action, the server outputs the action name and exact payload to the console and asks:

     ============================================================
     ⚠️  [ACTION PENDING APPROVAL]: append_to_doc
     ------------------------------------------------------------
     Payload:
     {
       "doc_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
       "content": "New analysis findings..."
     }
     ============================================================
     Approve? (y/n): 

     • Typing y (or Y) approves and executes the action.

     • Typing n (or any other input) rejects the action and returns 403 Forbidden with a rejection notification to the caller.

🚀 Setup & Installation

1. Prerequisites

• Python 3.9+

• A Google Account with access to Google Cloud Console

2. Google Cloud Setup & Credentials

1. Go to the Google Cloud Console.

2. Create a new project (e.g., google-mcp-server).

3. Enable the required APIs:

   • Search for Google Docs API and click Enable.

   • Search for Gmail API and click Enable.

4. Configure the OAuth Consent Screen:

   • Go to APIs & Services > OAuth consent screen.

   • Select External (or Internal for Google Workspace) and click Create.

   • Enter an App name (e.g., Google MCP Server) and your support email.

   • In Scopes, add:

     • .../auth/documents

     • .../auth/gmail.compose

   • In Test users, add your own Google email address (if external/testing mode).

   • Save and continue.

5. Create OAuth 2.0 Credentials:

   • Go to APIs & Services > Credentials.

   • Click + CREATE CREDENTIALS > OAuth client ID.

   • Application type: Desktop app.

   • Name: MCP Desktop Client.

   • Click Create.

   • Click DOWNLOAD JSON and rename the downloaded file to credentials.json.

   • Place credentials.json in the root directory of this repository (c:\MCP-SERVER\credentials.json).

3. Install Dependencies

Create a virtual environment (recommended) and install dependencies:

# Optional: create virtual environment
python -m venv venv

# Windows activate:
venv\Scripts\activate

# Linux/macOS activate:
source venv/bin/activate

# Install requirements
pip install -r requirements.txt

💻 Running the Server

Start the server using python or uvicorn:

python server.py

Or:

uvicorn server:app --host 127.0.0.1 --port 8000 --reload

Once running:

• API Base URL: http://127.0.0.1:8000

• Interactive Swagger UI Docs: http://127.0.0.1:8000/docs

• ReDoc Documentation: http://127.0.0.1:8000/redoc

Note on First Run: The first time you make a request (or run python auth.py), a browser window will automatically open asking you to log into Google and grant permissions. Once granted, a token.json file is saved locally so all subsequent requests run without browser interaction.

📡 API Usage & Endpoints

1. Root & Health Check

GET /

Returns server status and registry of available MCP tools.

curl -X GET http://127.0.0.1:8000/

Response:

{
  "server": "Google Docs & Gmail MCP Server",
  "version": "1.0.0",
  "status": "online",
  "tools": [
    {
      "name": "append_to_doc",
      "endpoint": "/append_to_doc",
      "method": "POST",
      "description": "Appends text content to an existing Google Document.",
      "required_parameters": ["doc_id", "content"]
    },
    {
      "name": "create_email_draft",
      "endpoint": "/create_email_draft",
      "method": "POST",
      "description": "Creates a draft email in Gmail.",
      "required_parameters": ["to", "subject", "body"]
    }
  ]
}

2. Append Content to Google Doc

POST /append_to_doc

Request Body:

{
  "doc_id": "YOUR_GOOGLE_DOC_ID",
  "content": "\n## Summary\nHere is the newly appended text.\n"
}

cURL Example:

curl -X POST http://127.0.0.1:8000/append_to_doc \
  -H "Content-Type: application/json" \
  -d '{
    "doc_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
    "content": "\n\n### Appended Section\nAutomated analysis report generated."
  }'

Terminal Prompt:

============================================================
⚠️  [ACTION PENDING APPROVAL]: append_to_doc
------------------------------------------------------------
Payload:
{
  "doc_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
  "content": "\n\n### Appended Section\nAutomated analysis report generated."
}
============================================================
Approve? (y/n): y
✅ Action APPROVED. Executing...

Success Response (HTTP 200):

{
  "status": "success",
  "message": "Successfully appended 64 characters to document 'Product Review Summary'.",
  "data": {
    "status": "success",
    "document_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
    "document_title": "Product Review Summary",
    "characters_appended": 64
  }
}

Rejection Response (HTTP 403):

{
  "detail": {
    "status": "rejected",
    "message": "Action 'append_to_doc' was not approved by the operator in terminal.",
    "payload": {
      "doc_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
      "content": "..."
    }
  }
}

3. Create Gmail Draft

POST /create_email_draft

Request Body:

{
  "to": "recipient@example.com",
  "subject": "Weekly Report Draft",
  "body": "Hi Team,\n\nPlease review the draft attached.\n\nBest,\nSai"
}

cURL Example:

curl -X POST http://127.0.0.1:8000/create_email_draft \
  -H "Content-Type: application/json" \
  -d '{
    "to": "team@example.com",
    "subject": "Weekly Review Draft",
    "body": "Hello,\n\nPlease find the review draft in your mailbox."
  }'

Terminal Prompt:

============================================================
⚠️  [ACTION PENDING APPROVAL]: create_email_draft
------------------------------------------------------------
Payload:
{
  "to": "team@example.com",
  "subject": "Weekly Review Draft",
  "body": "Hello,\n\nPlease find the review draft in your mailbox."
}
============================================================
Approve? (y/n): y
✅ Action APPROVED. Executing...

Success Response (HTTP 200):

{
  "status": "success",
  "message": "Successfully created Gmail draft (ID: r-1234567890) for 'team@example.com'.",
  "data": {
    "status": "success",
    "draft_id": "r-1234567890",
    "message_id": "18d1a2b3c4d5e6f7",
    "to": "team@example.com",
    "subject": "Weekly Review Draft"
  }
}

🧪 Testing Suite

You can run automated unit tests that verify all endpoints, authentication handling, Google Docs appending, and Gmail draft generation using mock Google API services:

pytest -v

🔒 Security Best Practices

• credentials.json contains your client secret and token.json contains refresh tokens granting access to your Docs and Gmail.

• Both files are ignored in .gitignore — never commit them to public version control.

• The interactive terminal approval mechanism acts as a guardrail against unauthorized or unintended agent actions.

☁️ Cloud Deployment (Railway)

To deploy this MCP server to Railway as a 24/7 cloud API service:

• Complete step-by-step instructions, environment variable setup (GOOGLE_TOKEN_JSON, GOOGLE_CREDENTIALS_JSON, REQUIRE_TERMINAL_APPROVAL=false), and security options are detailed in deployment.md.