Google Sheet MCP Server

Google Sheet MCP Server

Enables AI agents to read, write, and manage Google Sheets using the Google Sheets API v4.

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Google Sheet MCP Server

An MCP (Model Context Protocol) server that allows AI agents to read, write, and manage Google Sheets using the Google Sheets API v4.

Features

  • List Sheets: Retrieve a list of all sheets in a spreadsheet with their names, IDs, and grid properties.
  • Read Content: Read data from specific sheets or ranges, returned as formatted Markdown tables.
  • Write Content: API to create sheets, append data, and add columns.
  • Manage Structure: Rename sheets and delete sheets, columns, or rows.

Prerequisites

  • Python: 3.12 or higher
  • Package Manager: uv (recommended) or pip
  • Google Cloud Project:
    • "Google Sheets API" enabled.
    • Service Account created with a JSON key file.
  • Access: The Service Account email MUST have "Editor" access to the target Google Sheet to perform write operations.

Getting service-account-key.json

  1. Create Project: Go to Google Cloud Console and create a new project.
  2. Enable API: Search for "Google Sheets API" and click Enable.
  3. Create Service Account:
    • Go to IAM & Admin > Service Accounts.
    • Click Create Service Account.
    • Name it (e.g., sheet-mcp-bot) and click Create and Continue.
    • Grant "Editor" role, then click Done.
  4. Generate Key:
    • Click on the newly created Service Account email.
    • Go to the Keys tab > Add Key > Create new key.
    • Select JSON and click Create.
    • The file will download automatically. Rename it to service-account-key.json.
  5. Share Sheet: Open your target Google Sheet, click Share, and paste the Service Account email (found in the JSON file under client_email) with Editor permissions.

Installation

  1. Clone/Open this repository.
  2. Install dependencies:
    uv sync
    # or
    pip install mcp pandas python-dotenv google-api-python-client google-auth
    

Configuration

  1. Service Account: Place your Google Service Account JSON key in the project root and name it service-account-key.json (or update .env to point to its path).
  2. Environment Variables: Create a .env file:
    SPREADSHEET_ID=your_spreadsheet_id_here
    SERVICE_ACCOUNT_FILE=service-account-key.json
    
    Tip: The Spreadsheet ID is the long string in your sheet's URL: https://docs.google.com/spreadsheets/d/SPREADSHEET_ID/edit

Usage with MCP Clients

Option 1: Using uvx (Recommended)

This method allows you to run the server directly from GitHub without cloning the repository manually.

Add this configuration to your MCP settings file (e.g., claude_desktop_config.json or mcp_config.json):

{
  "mcpServers": {
    "google-sheet": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/vfh-tech/gsheet-mcp",
        "sheet-mcp"
      ],
      "env": {
        "SPREADSHEET_ID": "your_spreadsheet_id_here",
        "SERVICE_ACCOUNT_FILE": "C:\\path\\to\\your\\service-account-key.json"
      }
    }
  }
}

Option 2: Local Installation

If you prefer to clone the repository and run it locally:

{
  "mcpServers": {
    "google-sheet": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/sheet-mcp",
        "run",
        "sheet-mcp"
      ],
      "env": {
        "SPREADSHEET_ID": "your_spreadsheet_id_here",
        "SERVICE_ACCOUNT_FILE": "service-account-key.json"
      }
    }
  }
}

Testing

A verification script is included to test the connection and tools:

uv run test_server.py

Tools Available

Read Operations

  • list_sheets(): Lists all sheets in the configured spreadsheet.
  • read_sheet_data(sheet_name: str, range_name: str = None, last_20_rows: bool = False): Reads data from the specified sheet. Set last_20_rows=True to read only the last 20 rows (plus header).

Write Operations

  • create_sheet(title: str): Creates a new sheet (tab).
  • rename_sheet(old_title: str, new_title: str): Renames an existing sheet.
  • append_data(sheet_name: str, values: List[List[Any]]): Appends rows of data to the bottom of a sheet.
  • add_column(sheet_name: str, header: str, values: List[Any] = None): Adds a new column to the right of the existing data, with an optional header and values.

Delete Operations (Destructive)

  • delete_sheet(sheet_name: str): Deletes an entire sheet.
  • delete_row(sheet_name: str, start_index: int, end_index: int): Deletes rows within a specified range.
  • delete_column(sheet_name: str, start_index: int, end_index: int): Deletes columns within a specified range.

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