
Query your CSVs and Google Sheets from any AI agent, over MCP or a REST API.
A startup from the Netherlands, founded by Killian.
This page is designed to help you find out whether datatomcp is good and if it is the right choice for you.
datatomcp turns a CSV file or Google Sheet into a data source that AI agents and apps can query.
Upload a CSV, paste a CSV link or pick a Google Sheet. The data is loaded into a database (DuckDB), and an import report lists problems such as broken lines, numbers stored as text and mixed date formats before any agent sees the data.
AI agents like Claude, ChatGPT, Cursor and VS Code connect through a remote MCP server with OAuth sign-in, so there is no API key to paste. They can filter rows, group them and calculate counts, sums and averages. The database does the math, so totals are exact, and every result says which version of the data it used. Apps and automation tools like n8n or Make run the same queries over a REST API.
Access is read-only and raw SQL is not allowed. Private Google Sheets are shared through Google's file picker, one file at a time. The service is hosted in the EU, and data is never sent to AI providers or used for training.
Free plan: 3 datasets of up to 100,000 rows and 1,000 queries a day. Pro ($12 or €12 a month): 25 datasets of up to 2 million rows, 50,000 queries a day and hourly Google Sheets sync.
Listed in
Remote MCP server
Streamable HTTP with OAuth sign-in, works in Claude, ChatGPT, Cursor, VS Code and other MCP clients
REST API
Same queries over HTTPS with API keys, for apps, n8n and Make
Google Sheets sync
Pick a private sheet in Google’s file picker; on-demand refresh, hourly on Pro
CSV import
Upload a file or paste a CSV link, up to 2 million rows per dataset on Pro
Import report
Flags broken lines, numbers stored as text and mixed date formats
Exact aggregates
Filter, group, count, sum, average, min and max computed by DuckDB
TypeScript and Node.js, Hono, DuckDB with Parquet files, SQLite, the official MCP TypeScript SDK (Streamable HTTP), Better Auth for OAuth, and Astro for the website. Hosted in the EU.
It gives AI agents query tools instead of raw rows. The agent asks for a filter or a total, and a database (DuckDB) computes it, so answers on 100,000-row sheets are exact. Every result includes the dataset version, and messy data is flagged in an import report before any agent sees it. The same dataset works in AI clients over MCP and in apps over a REST API.
Most Google Sheets API tools are built for reading and writing rows in apps. datatomcp is built for questions: filters, group-by and totals run on the server, and it works as a remote MCP server with OAuth in Claude, ChatGPT and Cursor. It is read-only by design and hosted in the EU. If you need to write rows back to a sheet, a CRUD tool like SheetDB or Sheety is a better fit.
People who keep business data in spreadsheets and want to ask an AI agent about it: operations and finance teams, analysts, founders, and developers building agents or automations in n8n or Make.
I kept pasting spreadsheets into Claude and ChatGPT and getting totals that were close but not right. The model reads the rows and estimates. So I built a small service that puts the file in a real database and gives the agent a few safe query tools. It is built and run by one person in the Netherlands.
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