Google Sheets MCP Server

Google Sheets MCP Server

Wraps the Google Sheets API for reading, appending, updating ranges and adding dropdowns, with an optional Gmail monitor to automate job application tracking.

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Google Sheets MCP Server

CI Python License: MIT

An MCP server that wraps the Google Sheets API -- list tabs, read ranges, append rows, overwrite ranges, and add dropdown (data validation) rules -- plus an optional scheduled script that scans Gmail for new messages matching a pattern and appends rows for the ones that match, skipping ones that look like rejections/negatives.

Originally built to maintain a job-application tracker (new interview/offer emails in, auto-filtered rejections out), but the server itself is generic: any project that needs programmatic Sheets read/write/dropdown access from an MCP client can use it as-is.

Features

  • list_sheet_tabs -- list tabs, their IDs, row/column counts
  • read_range -- read cell values from an A1-notation range
  • append_rows -- append rows after existing data
  • update_range -- overwrite an exact range
  • set_dropdown_validation -- add a dropdown (data validation list) to a column
  • monitor_job_responses.py -- optional incremental Gmail-to-Sheet monitor, safe to run on a schedule (dedupes via a local state file, skips rejections via keyword matching)

Architecture

flowchart LR
    client["MCP client<br/>(Claude Desktop, etc.)"] -->|stdio / streamable-http| srv["server.py<br/>(FastMCP)"]
    srv -->|service account| sheets["Google Sheets API"]
    mon["monitor_job_responses.py<br/>(cron / Task Scheduler)"] --> gm["gmail_client.py"]
    gm -->|OAuth, read-only| gmail["Gmail API"]
    mon -->|append_rows| srv

Two independent credential paths: the Sheets side uses a service account (sheets explicitly shared with it), while the Gmail side uses a personal OAuth "Desktop app" flow -- personal Gmail accounts can't delegate to a service account, so the monitor authenticates separately with a read-only scope.

Prerequisites

  • Python 3.10+
  • A Google Cloud project with the Google Sheets API enabled
  • A service account with a downloaded JSON key
  • The target spreadsheet shared with that service account's client_email as Editor

Installation

git clone https://github.com/JasonEckardt/google-sheets-mcp-server.git
cd google-sheets-mcp-server
pip install -e .
cp .env.example .env

For development (tests + lint):

pip install -e ".[dev]"

Edit .env:

GOOGLE_SERVICE_ACCOUNT_FILE=service_account.json
DEFAULT_SPREADSHEET_ID=your_spreadsheet_id_here

Place your service account key in this folder (matching the filename in .env). Never commit this file -- it's already gitignored.

Running the MCP server

Local / stdio (Claude Desktop, or any local MCP client)

python server.py

Claude Desktop config example (claude_desktop_config.json):

{
  "mcpServers": {
    "google-sheets": {
      "command": "python",
      "args": ["/absolute/path/to/server.py"]
    }
  }
}

Remote / Streamable HTTP

MCP_TRANSPORT=streamable-http python server.py

Some MCP clients (e.g. Claude's web/Cowork custom connectors) only accept remotely-hosted servers reachable over HTTPS, authenticated via OAuth 2.0 -- not a local stdio process and not a bare API key/bearer token. If you need that, you'll additionally need to:

  1. Host this server somewhere with a public HTTPS URL (Cloud Run, Fly.io, a small VPS, etc.).
  2. Put an OAuth 2.0 authorization server in front of it (the mcp Python SDK has built-in support for this via FastMCP(auth_server_provider=...), which handles /authorize, /token, and token verification for you -- you mainly need to implement client/token storage).

That's genuine infrastructure work, not a config toggle -- budget for it accordingly if your use case needs a hosted connector rather than local stdio.

Example: seeding a tracker sheet

examples/seed_tracker.py shows how to drive the server's tool functions directly from a plain Python script (no MCP client needed): it appends a few rows to a Tracker tab and adds a Status dropdown to column E. The data in it is fictional -- use it as a template.

Optional: scheduled Gmail monitor

monitor_job_responses.py searches Gmail for messages matching a keyword query, skips anything that looks like a rejection or that's already been processed, and appends the rest to the sheet with Status = "Needs Review" for you to confirm/correct.

Because personal Gmail accounts can't grant a service account access (domain-wide delegation only works on Google Workspace), it uses its own OAuth "Desktop app" credentials:

  1. Enable the Gmail API in the same (or a different) Google Cloud project.
  2. Create an OAuth client ID of type Desktop app, download it, save as gmail_client_secret.json in this folder.
  3. Run python monitor_job_responses.py once, interactively -- it opens a browser for one-time consent, then caches a refresh token in gmail_token.json so future scheduled runs don't need a browser.

Then schedule it with cron or Task Scheduler, e.g.:

0 8 * * * cd /path/to/repo && python3 monitor_job_responses.py >> monitor.log 2>&1

Limitation: classification is keyword-based, not a language model -- it can catch obvious rejection phrasing but won't reliably distinguish subtler cases. Treat Needs Review rows as a draft, not ground truth.

Development

ruff check .   # lint
pytest         # unit tests (pure functions only -- no Google credentials needed)

CI runs both on every push/PR via GitHub Actions; a Jenkinsfile is also included for running the same pipeline on a Jenkins instance.

Roadmap

  • OAuth 2.0 authorization layer for the streamable-http transport, so the server can be hosted publicly and registered as a remote MCP connector (the mcp SDK's auth_server_provider hook does most of the heavy lifting).
  • Smarter response classification -- replace the keyword/regex rejection filter with an LLM pass so subtle "no news yet" vs. "interview scheduled" cases are handled correctly.
  • Sheet-based dedupe state for the monitor, so scheduled runs don't depend on a local JSON state file.

Security

  • service_account.json, gmail_client_secret.json, gmail_token.json, and .env are gitignored -- keep it that way, they're all credentials.
  • The service account can only touch sheets/files explicitly shared with it.
  • The Gmail OAuth token is scoped read-only (gmail.readonly).
  • Rotate/revoke credentials in Google Cloud Console if ever exposed.

License

MIT -- see LICENSE.

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