Google Sheets MCP server for AI agents

The Google Sheets MCP server provides a Model Context Protocol connector that enables AI agents to interact directly with Google Sheets spreadsheets, allowing them to read, write, and manipulate spreadsheet data programmatically.

Installation

Follow these steps to set up the Google Sheets MCP server:

Clone the repository:

git clone https://github.com/mkummer225/google-sheets-mcp
cd google-sheets-mcp

Install dependencies:
```
npm install
```
Build the project:
```
npm run build
```
Set up OAuth credentials:
- Create a new project in Google Cloud Console
- Enable the Google Sheets API
- Configure the OAuth consent screen
- Create OAuth client ID credentials (Desktop application) with a redirect URI (e.g., http://localhost:3000/oauth2callback)
- Download the credentials and save as gcp-oauth.keys.json in the dist subdirectory
Start the MCP server:
```
npm run start
```
You'll be prompted to authenticate your Google account when necessary.

Configuration

To configure your AI agent to use the Google Sheets MCP server, add the following to your configuration:

{
    "mcpServers": {
    "google-sheets-mcp": {
      "command": "node",
      "args": [
        "/{path_to_dir}/google-sheets-mcp/dist/index.js"
      ]
    }
  }
}

After configuration, you can specify a spreadsheetId to work with or ask your agent to create a new spreadsheet.

Available Actions

Authentication

refresh_auth: Re-authenticate your Google Account when credentials expire

Spreadsheet Management

create_spreadsheet: Create a new Google Spreadsheet
rename_doc: Rename a Google Spreadsheet

Sheet Operations

list_sheets: List all sheets/tabs in a Google Spreadsheet
create_sheet: Create a new sheet/tab in a Google Spreadsheet
rename_sheet: Rename a sheet/tab in a spreadsheet

Reading Data

read_all_from_sheet: Read all data from a specified sheet
read_headings: Read the column headings from a sheet
read_rows: Read specific rows from a sheet
read_columns: Read specific columns from a sheet

Writing and Editing Data

edit_cell: Edit a single cell in a sheet
edit_row: Edit an entire row in a sheet
edit_column: Edit an entire column in a sheet
insert_row: Insert a new row at specified position
insert_column: Insert a new column at specified position

Each of these actions can be invoked by your AI agent to interact with Google Sheets documents after the MCP server is properly configured and running.

How to add this MCP server to Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "cursor-rules-mcp": {
            "command": "npx",
            "args": [
                "-y",
                "cursor-rules-mcp"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.