How to Connect Grafbase to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of Grafbase

You have a Google Sheet full of data — subgraph endpoint URLs catalogued from onboarding, API key records from an access review, schema check IDs pulled from a CI report. Getting that data into Grafbase, or pulling Grafbase's registry data back into your sheet, is not a one-click operation.

Grafbase is built for managing federated GraphQL APIs at scale: schema registry, composition checks, federation routing. But the gap between "Grafbase knows this" and "my spreadsheet shows this" is a manual process every single time. The default flow is logging into the dashboard, navigating to the right graph, exporting what you can, and pasting it somewhere — hoping you got the right branch and didn't miss a subgraph.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default. Log into the Grafbase dashboard, find the graph, navigate to the subgraphs list or schema registry, and transcribe what you see into your sheet by hand. If you want schema check history, you scroll through it, note the statuses, and retype the relevant rows.

For a one-time snapshot before a major deployment, that is survivable. You do it once, you move on.

But Grafbase data changes. Subgraphs get added. Schema checks accumulate on every commit. API keys get rotated. The moment this becomes a recurring task — weekly audit exports, monthly access reviews, quarterly compliance pulls — you are re-doing the same navigation sequence over and over. Each run feels like you are doing the same work someone already did last month. And you are.

Method 2: Zapier or Make

Grafbase exposes a GraphQL API. In theory, you can wire a Zap or Make scenario to query it on a schedule and write the results into your sheet.

Before going further — do you know what a GraphQL query looks like? Can you write a query with field selections, handle pagination cursors, and parse a nested JSON response into flat rows? If that feels unfamiliar, this is not your path. Method 4 is a better use of your time.

For the engineers who are still here: the flow works. You authenticate with a Grafbase API token, pick a trigger (a schedule, a webhook, an event), write the GraphQL query against the right graph slug and branch, parse the response, and map the fields to sheet columns. Make's HTTP module or Zapier's webhooks step can handle the call. The first run, when it works, feels good.

The catch is everything that comes after.

A trigger-per-row setup is not the same as a bulk export.

Pulling 40 subgraphs means 40 separate API calls, 40 task credits, and a history log that becomes impossible to trace when subgraph 17 returns a null endpoint and the rest silently skip it.

You probably just need the schema check history and you probably have no idea how to write a paginated GraphQL query against Grafbase's registry API — and that is completely reasonable. So you hand this off to whoever on your team builds automations, and now you are waiting on a Slack thread. If they have not gone quiet on you already.

And once you need to join subgraph data against check history or filter by branch, you have left Make's native field-mapping capabilities behind.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable spreadsheet ↔ API workflows was a category of add-ons that let you configure a saved query template, map the response fields to columns, and rerun it on demand. You picked your endpoint, you tagged your fields, you saved a config, you ran it.

That was a real step up from copy-paste. The output was consistent, the configs were reusable, and the team did not have to redesign the export every month.

But you were still responsible for the GraphQL query, the field mapping, the pagination logic, the conditional filtering about which subgraphs to include, the column renaming when Grafbase's schema changed. The tool got the data through, but every decision about what to pull and how was still yours to make. And when Grafbase updated a field name or the team renamed a graph, your config broke until someone went in and patched it.

This is the previous generation. It worked, but it asked a lot of the operator.

The Easy Way: Using SheetXAI in Google Sheets

There is a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands what you are looking at, and through its built-in Grafbase integration it can push to or pull from Grafbase for you. No template configuration, no automation glue, no manually composing GraphQL queries. You just ask.

Example 1: Pull all subgraphs into the sheet

List all published Grafbase subgraphs for account my-org and write each subgraph's name, endpoint URL, and branch into columns A–C of Sheet1

The response lands in rows immediately — subgraph name in A, endpoint URL in B, branch identifier in C. No query to write, no pagination to handle.

Example 2: Export schema check history with a summary

Fetch the last 100 schema checks for Grafbase graph production-api and write each check's ID, status, git commit, and approval state into Sheet1 as rows, then count how many passed vs. failed this month and write a two-row summary table in Sheet2

The pattern: instead of pulling the raw data first and then writing a summary formula, you ask for both in one prompt. SheetXAI handles the filtering and aggregation inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet where you track Grafbase graph metadata, then ask it to do one of the tasks above. The Grafbase integration is included in every SheetXAI plan.