How to Connect Grafbase to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Grafbase

You have an Excel workbook 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 workbook, 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 workbook 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 did not 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 workbook by hand. For schema check history, scroll through the dashboard, note the statuses, and retype the relevant rows. CSV exports exist for some views, which helps — but you still have to open them, reformat the columns to match your workbook structure, and paste them into the right worksheet.

For a one-time snapshot before a major deployment, that is survivable.

But Grafbase data changes constantly. 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 import sequence over and over. The reformatting alone costs you thirty minutes you should not have to spend. And you still end up re-doing it next week.

Method 2: Power Automate

Grafbase exposes a GraphQL API. In theory, you can build a Power Automate flow to query it on a schedule and write the results into your Excel workbook.

Before going further — are you comfortable with HTTP actions, authentication headers, and parsing JSON responses into dynamic content? Do you know what a GraphQL query body looks like and how to handle pagination in a loop? If those questions feel unfamiliar, this is not the right path for you. Method 4 is where you want to go.

For those who work with Power Automate regularly: the flow is buildable. You create an HTTP action, add a Grafbase API token in the Authorization header, write the GraphQL query, parse the response with a Parse JSON step, and use an Apply to Each to write rows into Excel. The first run, when it works, is satisfying.

What comes after is the friction.

A row-by-row loop is not the same as a bulk export.

Pulling 40 subgraphs inside an Apply to Each means 40 HTTP calls, 40 runs in your flow history, and a run log that becomes impossible to debug when subgraph 22 returns an unexpected null and the rest continue silently.

You probably just need the schema check history for the engineering manager's review, and you probably have no idea how to structure a paginated GraphQL query inside a Power Automate loop — and that is not a gap you should have to close. So you hand this off to whoever on your team manages these flows, and now you are waiting on a Slack message. If they have not deprioritized it already.

And once you need to join subgraph data against check history or filter by date range across worksheets, you have left Power Automate's native capabilities behind entirely.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable workbook ↔ 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, tagged your fields, saved a config, and ran it.

That was a real step up from copy-paste. The output was consistent, 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, and 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 Excel

There is a different way entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, 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 workbook

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 with counts and pass rate percentage

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 Excel workbook 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.