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Google Cloud Natural Language n8n integrationAutomate Google Cloud Natural Language with n8n.

Nobody should spend their morning reading messages to sort the angry ones from the rest. The Google Cloud Natural Language n8n integration hands that pass to the API: one node, one action, Analyze sentiment on the Document resource. No trigger node ships with it, so the analysis sits mid-workflow.

Try the Google Cloud Natural Language integration on n8nSee the 1 operations

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Why automate

What does the Google Cloud Natural Language n8n integration cover?

It wires the Google Cloud Natural Language API into any n8n workflow through a single node action, document.analyzeSentiment, filed under the Document resource. You hand it text, either a string the workflow already carries or a file sitting in Google Cloud Storage, and the API analyzes the sentiment of that text. The node ships with n8n, so there is nothing to install on n8n Cloud or on a self-hosted instance.

Start with the support inbox, because that is where free text piles up fastest. A Gmail node pulls the morning's messages, the Document node reads each body through the Content field, and the branch that follows decides what a person opens first. The text is never retyped, never pasted into a browser tab, never read twice.

Second pattern: the survey export nobody has time to skim. A Schedule Trigger, the n8n node that fires on a fixed interval, opens a Google Sheets tab every morning and walks the new rows. Each comment goes through the node with Source set to Content, and the result travels back to the sheet or straight into a Slack channel where the team already works.

Third pattern, and the one people forget: long documents that never belonged in a spreadsheet cell. Meeting notes, transcripts, exported PDFs converted to text. Drop them in a bucket, set Source to Google Cloud Storage URI, and point Google Cloud Storage URI at gs://bucket_name/object_name. The workflow moves a path around instead of a wall of characters.

The catalogue holds one operation for this node. Anything else you want from the Google Cloud Natural Language API goes through the HTTP Request node, which calls any endpoint of the API and reuses the same credential through predefined authentication. That fallback is a standard n8n move, not a workaround.

Here is the first thing to do, before wiring anything downstream. Drop the node after any trigger, leave Source on Content, map Content to the field carrying your text with an expression like {{ $json.field }}, and execute the node once on a single item. Read what comes back in the output panel, then build your branching on what you actually see there. Guessing the shape of the answer is how a workflow breaks two weeks later. If n8n itself is new to you, the n8n training covers expressions and credentials from scratch, and the n8n review walks through where the tool fits.

Connect

How do you connect Google Cloud Natural Language to n8n?

  1. 01

    Sign in with Google on n8n Cloud

    On n8n Cloud, the credential screen offers Managed OAuth2: click Sign in with Google and the connection is done. Nothing to configure in the Google Cloud Console, no client ID to copy. A credential is created once from the Credentials menu and reused by every workflow after that, and the node picks it up from its own dropdown.

  2. 02

    Build a Custom OAuth2 credential when you self-host

    Managed OAuth2 is not available on self-hosted n8n, so you create a Google OAuth2 single service credential yourself. In the Google Cloud Console: create a project, enable the API, configure the OAuth consent screen with an App name and a User support email, then add your authorized domain, n8n.cloud for Cloud or the domain of your instance.

  3. 03

    Copy the redirect URL, then the client ID and secret

    Create an OAuth client ID with Application type set to Web application. Copy the OAuth Redirect URL shown in your n8n credential and paste it into Authorized redirect URIs in Google, then bring the Client ID and Client Secret back to n8n. Running n8n locally works too: Google accepts http://localhost:5678/rest/oauth2-credential/callback as a redirect URI.

Actions

What can the Google Cloud Natural Language node do?

The Google Cloud Natural Language node exposes 1 operations across 1 resources. For each one: the node as you configure it in n8n, the required fields, and our field notes.

Resources × operations matrix
ResourceAnalyze Sentiment
Document✓

Document

1 operation
01

Analyze sentiment

document.analyzeSentiment

What you see in n8n

Notes & use cases

One action, one job: text in, the API's sentiment analysis out.

Key parameters

  • Source: where the text comes from, content for a string or gcsContentUri for a Cloud Storage file.
  • Content: the text itself, usually mapped with {{ $json.field }}.
  • Google Cloud Storage URI: the file path, as gs://bucket_name/object_name.
  • Document Type: Plain Text or HTML, so page tags are not read as words.
  • Encoding Type: None, UTF-8, UTF-16 or UTF-32, used to calculate sentence offsets.
  • Language: empty means detected, or one of the 16 codes, ISO or BCP-47.
Use cases
survey comments run through one row at a time, and the branch after decides which ones a human opens.
Need help

Need help automating Google Cloud Natural Language with n8n?

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FAQ

Google Cloud Natural Language and n8n, the questions that come up

01Is the Google Cloud Natural Language n8n integration free?
On the n8n side, yes. The node ships with n8n, so there is no plugin to install and no extra cost from n8n to use it. That holds on n8n Cloud, the hosted offer run by n8n, and on a self-hosted instance installed with Docker or npm under the Community Edition and its Sustainable Use license. A workflow behaves the same way in both places, which means you can prototype on one and run it on the other. What the Google side costs is a separate question, settled in your Google Cloud account rather than here.
02Which credentials does the node need?
A Google OAuth2 single service credential. On n8n Cloud the fastest path is Managed OAuth2: click Sign in with Google in the credential screen and nothing else is required. Self-hosted instances go the Custom OAuth2 route, which means a Google Cloud Console project, the API enabled, an OAuth consent screen, and an OAuth client ID of type Web application whose Client ID and Client Secret you paste into n8n. A Service Account credential is the other documented option: create the key, download the JSON file, then copy client_email into Service Account Email and private_key into Private Key, without the surrounding quote marks. You create the credential once and every workflow reuses it.
03What are the limits of the Google Cloud Natural Language node?
The catalogue exposes one operation, Analyze sentiment, on a single resource, Document. Everything else you might want from the Google Cloud Natural Language API is reached with the HTTP Request node, which calls any endpoint of the API and reuses the same credential through predefined authentication. Plan for that node from the start if your project needs more than one kind of analysis. On the input side, remember that Content expects a string: an item that arrives with an empty value in a required field stops the node, since a field marked required blocks execution when it is empty.
04How do you trigger a Google Cloud Natural Language workflow?
With another node, because this tool has no trigger node in n8n. Three usual starting points. A Schedule Trigger runs the workflow on a fixed interval, which suits a nightly pass over a spreadsheet or a bucket. The n8n Webhook node gives you a URL that a third-party service calls, so the workflow starts when that service has something to say. Or you start from the trigger of another tool entirely, a new email, a new row, a new message, and the Document node becomes the second step. The analysis itself is the same in all three cases.
05n8n or Make for Google Cloud Natural Language?
It depends on where you want the workflow to live. Make is a hosted automation platform with no self-hosting option, billed per operation, so the cost follows your volume and the data passes through their infrastructure. n8n runs the same workflow on n8n Cloud or on your own server with Docker or npm, which matters when the text you analyze is customer correspondence you would rather keep in house. Both build workflows visually. Pick on three criteria: where the data sits, how the cost scales with volume, and how comfortable your team is maintaining an instance.
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