Google Sheets MCP server: hosted, no Google Cloud setup
Most Google Sheets MCP servers are local processes. You create a Google Cloud project, enable the Sheets API, make a service account, share the sheet with its email address, download a JSON key and run the server next to your editor. That works on your machine and nowhere else.
datatomcp is a hosted MCP server for your sheets. There is nothing to install and no Google Cloud setup, and it works in every MCP client that supports remote servers: Claude Code, Cursor, Claude.ai, Claude Desktop and others.
How it differs from a local Sheets MCP
| Local Sheets MCP (typical) | datatomcp | |
|---|---|---|
| Setup | Google Cloud project, service account, JSON key | Sign in with Google, pick the sheet |
| Access | Sheets shared with the service account | Only the files you pick (drive.file) |
| Runs | On your machine, per client | Hosted, one URL for every client |
| Big tabs | Tool returns raw cell ranges | Filters and totals computed server-side |
| Writes | Often read and write | Read-only, by design |
If you need an agent to edit cells, a local server is the right tool. If your agents need to answer questions from sheet data, a read-only query server is safer and more accurate.
1. Import the sheet
Sign in at app.datatomcp.com, then Add data → Google Sheet → Choose a Google Sheet. The import report shows each column’s type and any data problems before agents see it.
2. Add the server to your client
The server URL is the same for every client: https://app.datatomcp.com/mcp (Streamable HTTP, OAuth).
Claude Code
claude mcp add --transport http datatomcp https://app.datatomcp.com/mcpRun /mcp, choose datatomcp and authenticate in the browser.
Cursor
Open Settings → MCP → Add new server, choose type HTTP and use the URL above. Cursor asks you to log in the first time it connects. (We test every release with Claude Code and Claude.ai; Cursor uses the same remote MCP standard.)
Claude.ai and Claude Desktop
Settings → Connectors → Add custom connector, paste the URL, connect and allow access. See Connect Google Sheets to Claude for the full walkthrough.
3. The tools your agent gets
| Tool | What it does |
|---|---|
list_datasets |
Every dataset the account can read, with row counts and freshness |
describe_dataset |
Columns, types, example values, data warnings and today’s date |
query_rows |
Filter, sort, select columns, paginate (up to 1,000 rows per call) |
aggregate |
Group by columns; count, distinct count, sum, average, min, max |
distinct_values |
The real values in a column, so filters match exactly |
Filters support eq, neq, gt, gte, lt, lte, in, not_in, contains, starts_with, between, is_null and not_null. Agents can’t run SQL: the tools are validated and capped, so a confused agent can’t run something slow.
Example
Which product had the highest revenue in Q3, and by how much?
The agent calls aggregate with group_by: ["product"], a between filter on the date and order_by on the revenue metric, then reports the top rows. Every result includes meta.version, so you can tell which sync of the sheet the answer came from.
Sync
Refresh now re-reads the sheet on demand. Pro syncs every hour and skips unchanged sheets, so versions only change when your data does.