datatomcp

Add your spreadsheet to ChatGPT as a custom MCP connector

By Killian Helf, founder · Updated 19 October 2026 · Markdown

ChatGPT can analyze a file you upload, but each upload is a one-off copy: it doesn’t stay in sync, it has size limits, and totals depend on the code ChatGPT writes that time. A custom MCP connector lets ChatGPT query a dataset that lives elsewhere and stays current. This guide connects a CSV or Google Sheet through datatomcp.

What you need

  • A ChatGPT plan with custom connectors (developer mode). Availability and menu names change; check OpenAI’s help pages if yours differ.
  • A datatomcp account with at least one dataset. Import a CSV, a CSV link or a Google Sheet under Add data.

1. Turn on developer mode

In ChatGPT, open Settings → Apps & Connectors → Advanced and enable developer mode.

2. Create the connector

  1. Under Apps & Connectors, choose Create.
  2. Name: datatomcp. MCP server URL: https://app.datatomcp.com/mcp.
  3. Authentication: OAuth. ChatGPT registers itself with datatomcp automatically.
  4. Save, then connect: a datatomcp sign-in and a consent screen appear. Allow read access to your datasets.

3. Use it in a chat

Enable the connector for the conversation and ask:

Using datatomcp, what were total sales per country last quarter? Show the top five.

ChatGPT calls describe_dataset, then aggregate with a group_by on country, a date filter and a sum. The numbers come from the database, and the result names the dataset version used.

Tips

  • Ask ChatGPT to call distinct_values before filtering on a text column, so it uses the exact spelling in your data.
  • For row-level questions (“list the 20 largest orders”), it uses query_rows with order_by and limit.
  • The connector is read-only. ChatGPT can’t change your data.

Keeping data current

Click Refresh now on the dataset page after the source changes, or let Pro sync linked sources every hour.