Mindket

Encode API data to GCF and decode it back

Newversion 1 · updated

Overview

An n8n workflow that fetches a page of records from a public API, packs them into GCF text with a community node, and decodes the text back to compare. It needs a community node on a self-hosted n8n.

Encode API data to GCF and decode it back is an n8n workflow in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in
  • Your own n8n server: install n8n-nodes-gcf as an Owner or Admin, then import the file
  • n8n Cloud: only verified community nodes can be added, so check first whether this one is
  • Other workflows: put GCF Encode before a model call and send its data field in the prompt
  • Any JSON source: replace the API call with your own

Platform

Connects 2 apps

How it works

Trigger

Manual run

It starts when you press Execute workflow, and there is no form:

  • No input from you: the API address is set inside the workflow

Actions

  1. The workflow asks a public API for the first 100 contributors of one repository
  2. A Code node gathers the 100 items into one item with a payload list
  3. GCF Encode turns the list into GCF text and adds an estimate of the tokens saved
  4. GCF Decode turns the text back into the list, so you can compare it with the original

Result

The packed GCF text with its size estimate, and the decoded list beside it

Integrations

What you need before you start.

GitHub

Public data source

Answers an unauthenticated request for the contributors of one repository, 100 to a page.

NeedsNothing: no account or token, at most 60 calls an hour

GCF

Community node

Encodes JSON to GCF text and decodes it back, with a token estimate on encode.

NeedsThe n8n-nodes-gcf community node, installed on a self-hosted n8n

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
5 steps, starting by hand
AI
No step calls an AI model
Sign-ins
No sign-in
API keys
No API key is left in the file
Community nodes
Needs the community node package n8n-nodes-gcf
Step types
Mindket’s checker reads 3 of its 4 step types. It does not read: Gcf

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow packs JSON into GCF, a compact text format that its makers say costs a language model fewer tokens, and then unpacks it again. A press of the button fetches the top 100 contributors of one open source repository from a public API, gathers them into one list, encodes the list and decodes the text back. The encode step reports an estimate of the tokens saved. Five nodes do the work, and none is a sticky note.

Who it suits

Developers who send API data to a language model and want to see what a smaller format would save. Skip it if you run n8n Cloud, because it needs a community node that Cloud may not allow. It is a measuring rig, not a service.

Who uses it, and how
IndustryWho uses itHow they use itExample
SoftwareAI engineersMeasure how much a tool’s JSON shrinks before a model reads itAn engineer encodes an API reply and reads the token estimate.
DataData engineersCheck that a compact format round-trips their recordsA data engineer decodes the text and compares it with the original list.
OperationsAutomation buildersCut the size of data that goes into an agent’s promptA builder encodes a ticket export before an agent reads it.
ResearchPrompt researchersCompare sizes on their own dataA researcher swaps in their own source and notes the percent saved.

You need a little n8n and the right to install a community node.

Where to use it

A self-hosted n8n where you can install a community node will run it. The results appear in the output of the last two nodes.

  • Your own n8n server: install n8n-nodes-gcf as an Owner or Admin, then import the file
  • n8n Cloud: only verified community nodes can be added, so check first whether this one is
  • Other workflows: put GCF Encode before a model call and send its data field in the prompt
  • Any JSON source: replace the API call with your own

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Setup is one community node and no credential.

What you need first
NeedDetail
n8nA self-hosted one, where an Owner or Admin can install community nodes
Community noden8n-nodes-gcf, installed under Settings, then Community Nodes
  1. In n8n, open Settings, then Community Nodes, then Install. Type n8n-nodes-gcf and accept the notice. Restart n8n if it asks you to.
  2. Create a workflow, open its menu, choose Import from File and pick workflow.json.
  3. Press Execute workflow.
  4. Open GCF Encode for the packed text and the size estimate, and GCF Decode (lossless) for the decoded list.

How to use it

Press the button and read the two outputs. To use your own data, point the first node at another JSON API. If you rename the payload field, change it in the Code node and in GCF Encode together. Switch the token metrics option off when you only need the text.

What to change for a different result
To changeWhere
The data sourceThe address in GET /contributors (100 records)
The field that holds the listpayload in Batch into Array and in GCF Encode
The size estimateThe token metrics option in GCF Encode
The decoded fieldThe output field of GCF Decode (lossless)

Example

An engineer runs it to see what a page of contributor records costs as JSON and as GCF.

GCF Encode outputs data, the packed text, and tokenMetrics, which holds the estimated tokens as JSON and as GCF, the tokens saved and the percent saved. GCF Decode (lossless) outputs decoded, the list again. Treat the estimate as a rough guide.

For newcomers and experts

If you are new. A token is a piece of text that a language model counts and bills for. A compact format can mean fewer tokens for the same data. This workflow lets you measure that on real data instead of trusting a claim.

For experts. Two nodes come from the community package, GCF Encode and GCF Decode (lossless). The node reads its input field as a path into the item, so payload names the field of that name. The token figures are the text length divided by four, rounded up, and not a tokenizer’s count.

Where to look closer
NodeWhat it doesWhat to know
GET /contributors (100 records)Calls a public contributors endpointCalls without a token are limited to 60 an hour per address
Batch into ArrayGathers the items into one payload listThe encoder takes one list, not many items
GCF EncodeWrites the list as GCF text in datatokenMetrics appears only on this output
GCF Decode (lossless)Reads data back into decodedIt outputs decoded alone, and lossless is the node’s own claim

Good to know

The workflow needs a community node, which reaches further than a built-in one.

  • Community node: n8n-nodes-gcf runs on your server with the same reach as n8n, so it can touch the data in every workflow. n8n does not review it. Only an Owner or Admin of a self-hosted n8n can install it, and n8n Cloud accepts verified community nodes only
  • What we checked: we read version 0.1.3, which is MIT licensed, has no install scripts, and makes no network, file or process calls in its node code. It is a new package with one maintainer. We did not read later versions, so read the one you install
  • Rate limit: the call carries no token, and the host allows 60 such calls an hour from one address. A page holds at most 100 records, and the list can be hours old
  • The estimate: the token figures are not a tokenizer’s count, and the node’s own claims of large savings are not checked here
  • No model, no key: the workflow calls no model and holds no credential
  • Your data: the public API sees only the request, and the records stay in your n8n

README and files

README

Encode API data to GCF and decode it back

An n8n workflow that fetches a page of records from a public web API and packs them into one short block of text in the GCF
format. It then turns that text back into data, so you can see nothing was lost. Use it to measure how much smaller a payload
gets before you send it to a language model.

It needs a community node, n8n-nodes-gcf, which does not ship with n8n. Read "Before you start" first.

What is inside

  • workflow.json: the workflow as n8n exports it, 5 nodes and no sticky notes. It holds no credential and no private address.
  • README.md: these notes.

What we changed from the original copy

  • Nothing in the nodes. The file held no credential, no key and no code that needed repair.
  • The export's tags and its setup flag are gone, so the workflow opens with no tags and no saved sample data.

Before you start

  • A self-hosted n8n. Community nodes install on n8n you run yourself. On n8n Cloud only verified community nodes can be added,
    and we did not confirm that this one is verified.
  • The owner or an admin of that n8n installs the node: Settings, Community Nodes, Install, then type n8n-nodes-gcf and accept
    the notice.
  • Read the notice before you accept it. A community node runs on your server with the same reach as n8n itself, so it can touch
    the data in every workflow and every file n8n can read. n8n does not review it.
  • What we checked: we read version 0.1.3 of the package, which is MIT licensed, has no install scripts, and asks only for n8n's
    own library and one small encoder library. Its code makes no network, file or process calls. It is a new package with one
    maintainer, and we did not read any later version. Read the version you install.
  • No account and no key. The API in the workflow is public.

Set it up

  1. Install the community node as above, then restart n8n if it asks you to.
  2. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
  3. Press Execute workflow.
  4. Open GCF Encode to read the packed text and the size comparison. Open GCF Decode (lossless) to see the data come back.

How a run goes

  1. When clicking 'Execute workflow' starts the run by hand.
  2. GET /contributors (100 records) asks a public web API for the contributor list of one open source repository, 100 records
    per page. The API gives back one item per contributor.
  3. Batch into Array is a Code node. It gathers those items into one item with a single field, payload, that holds the list.
  4. GCF Encode reads payload and writes its GCF text to the field data. The option for token metrics is on, so the item
    also carries tokenMetrics: the estimated size of the data as JSON and as GCF, the tokens saved and the percent saved.
  5. GCF Decode (lossless) reads data and writes the unpacked list to the field decoded.

Change the look

  • The source: change the address in GET /contributors (100 records) to any API that returns JSON. Keep payload as the field
    name, or change it in Batch into Array and in GCF Encode together.
  • The size check: switch the token metrics option off in GCF Encode when you only need the text.
  • The use: put GCF Encode before a model call and send data in the prompt instead of the JSON. Nothing in this file calls a
    model.

Good to know

  • Rate limit: the call is unauthenticated, and the host allows 60 such calls an hour from one address. A run that is refused
    fails at the first node. A page holds at most 100 records, and the list can be a few hours old.
  • The token figures are an estimate: the length of the text divided by 4, rounded up. They are not a real tokenizer's count.
    They appear only on the output of GCF Encode. GCF Decode (lossless) outputs decoded alone.
  • The node's own page makes large savings claims. We did not verify them, so run this workflow on your own data to see yours.
  • The workflow depends on the node. If you remove it, or it fails to load, both GCF steps stop working.
  • No model and no cost: the run uses no paid service. The decode step lets you compare the unpacked list with the original.
    "Lossless" is the node's own claim, so check it on the shape of data you care about.
Files
NOTICE.md  636 B
README.md  4 KB
workflow.json  3 KB

3 files, 7 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

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