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Lexeri Community Node for n8n

Stefan Rohde
  • Updated

Overview

The Lexeri Community Node extends n8n with a direct connection to your Lexeri terminology database. This allows you to fully embed terminology processes into your existing automation workflows – without manual effort and without custom integration development.

With the node you can:

  • Automatically check texts for terminology violations
  • Search, import, export, and organize terms
  • Trigger term extraction jobs from documents
  • Create term suggestions (term requests)
  • React to events in your terminology database in real time (e.g. when a new term is added)

The node consists of two components: the Lexeri Action Node for active operations and the Lexeri Trigger Node for event-based triggers.

The community node is published here: npmjs.com/package/n8n-nodes-lexeri

Prerequisites

  • An active n8n account (self-hosted or n8n Cloud on the Starter plan or higher)
  • An active Lexeri account with access to the API settings
  • A Lexeri API token (bearer token) – how to create one is explained in the next section

Creating an API Token in Lexeri

  1. Log in to your Lexeri account.
  2. Go to the Termbase Settings.
  3. Open the API tab.
  4. Click Create New API Token and copy the generated token.

Note: The token is only displayed in full once. Save it securely before closing the window.

Installing the Node

In n8n (recommended)

  1. Open n8n and navigate to Settings → Community Nodes.
  2. Click Install.
  3. Enter the following value in the "Enter npm package name" field:
 
   n8n-nodes-lexeri
  1. Acknowledge the warnings and click Install.

After installation, the Lexeri node will appear in your node library and is ready to use immediately.

For self-hosted n8n instances (Docker)

If you run n8n in Docker, you can also deploy the node via a volume mount:

  1. Download the latest version of the package from npm.
  2. Extract the archive into a directory on your server (e.g. custom-nodes/n8n-nodes-lexeri).
  3. Add the following entries to your docker-compose.yml:
 
yaml
   environment:
     - N8N_COMMUNITY_PACKAGES_ENABLED=true
     - N8N_CUSTOM_EXTENSIONS=/home/node/.n8n/custom
   volumes:
     - ./custom-nodes/n8n-nodes-lexeri:/home/node/.n8n/custom/n8n-nodes-lexeri
  1. Restart the container: docker compose up -d

Configuring Credentials

Before you can use the node, you need to store your Lexeri API credentials in n8n:

  1. Click on the Lexeri node in a workflow.
  2. Under Credentials, click Create New.
  3. Select Lexeri API.
  4. Enter your Bearer Token from the previous step.
  5. Click Save and test the connection.

A green checkmark next to the credentials indicates a successful connection.

Available Actions (Action Node)

1. Check Terminology – Check Terminology

Checks a text against your terminology database and returns recommendations for any non-preferred terms found.

Parameters:

  • Text – The text to check (multi-line input supported)
  • Locale Code – Language code of the text (e.g. de, en, fr)
  • Suggestion Locale Code (optional) – Language code for terminology suggestions. Leave empty for suggestions in the same language; enter a different code for cross-language suggestions.
  • Simplified Output (default: enabled) – Returns a compact JSON format ideal for IF nodes and workflow branching.

Simplified Output (default):

 
json
{
  "has_forbidden_terms": true,
  "forbidden_count": 1,
  "total_matches": 1,
  "forbidden_terms": [
    {
      "found": "Luftdichtheit",
      "state": "not_recommended",
      "preferred": "Luftdichtigkeit",
      "usage": "Use 'Luftdichtigkeit' instead"
    }
  ],
  "locale_code": "de"
}

Use the full API output when you need access to all detailed information (e.g. misspellings, multiple matches).

2. Search Terms – Search Terms

Searches your terminology database for terms with extensive filtering options.

Key parameters:

  • Search Query – Search term (leave empty to return all terms)
  • Locale Code – Language filter (e.g. de, en)
  • Status – Filter by term status: preferred, admitted, not_recommended, outdated, not_selected
  • Term Type – fullForm, shortForm or abbreviation
  • Topic – Terms belonging to a specific subject area
  • Missing Translation – Returns only terms that do not yet have a translation in a given language code

3. Get Termbase Info – Get Termbase Info

Returns metadata and statistics about your terminology database (name, number of terms, available languages, etc.). No input parameters required.

4. Export Termbase – Export Termbase

Exports your entire terminology database as a TBX file (TermBase eXchange). The output is binary and can be saved, forwarded, or imported into other systems.

Use case: Backup, sharing with translation tools (e.g. memoQ, SDL Trados), migration.

5. Import Terms – Import Terms

Imports terms from a file in TBX, CSV, or XLSX format.

Parameters:

  • Input Binary Field – Name of the binary property containing the import file (default: data)
  • Description (optional) – Description of the import job

Note: The import runs asynchronously. The response contains an identifier and a token that can be used to check the import status.

6. Extract Terms from Documents – Extract Terms from Documents

Starts an AI-powered term extraction job based on uploaded documents.

Parameters:

  • Title – Name of the extraction job
  • Description (optional)
  • Locale Code – Language of the document
  • Input Binary Field – The document to be analyzed

Supported languages: German, English, Spanish, French, Italian, Portuguese, Dutch, Polish, Czech, Russian, Japanese, Chinese (Simplified), Korean.

7. Create Term Request – Create Term Request

Creates a collaborative term request with terminology candidates and optional reference documents.

Parameters:

  • Title – Name of the request
  • Locale Code – Language of the suggested terms
  • Term Suggestions – Comma-separated list (e.g. sustainability, eco-friendly, carbon neutral)
  • Term Type, Part of Speech, Grammatical Gender, Number (all optional)
  • Usage Note & Definition (optional)
  • Reference Document (optional) – Binary field with accompanying documents

8. Create Usage Example – Create Usage Example

Adds a contextual usage example to a term.

Parameters:

  • Term Identifier – Required field
  • Example Text – The term in context (required)
  • Source (optional) – Origin of the example (e.g. "Product Manual v3.0")

10. List Topics – List Topics

Returns all subject areas in your terminology database. Topics can be used to categorize terms.

11. Add Terms to Topic – Add Terms to Topic

Assigns multiple term entries to a specific subject area.

Parameters:

  • Topic Identifier – The ID of the subject area
  • Term Entry Identifiers – Comma-separated list of term entry IDs

Trigger Node

The Lexeri Trigger Node allows workflows to react in real time to events in your terminology database. n8n automatically registers a webhook with Lexeri when the workflow is activated – and removes it when deactivated.

Available Events

Term Created – Triggered when a new term is added to the terminology database.

 
json
{
  "action": "term_created",
  "payload": {
    "identifier": "term-abc123",
    "termbase_identifier": "termbase-456",
    "updated_term_entry_identifiers": ["entry-789"]
  }
}

Term Request Created – Triggered when a new term request is created.

 
json
{
  "action": "term_request_created",
  "payload": {
    "identifier": "request-abc123",
    "termbase_identifier": "termbase-456",
    "user_name": "max.mustermann",
    "title": "Q2 Marketing Terms",
    "description": "Terminology for the product launch"
  }
}

Optional: Filtering by Resource ID

Both triggers support optional filtering by a specific term or term request ID. Filtering is handled at the n8n level (after the webhook is received).

Webhook Setup

  1. Add the Lexeri Trigger Node to your workflow.
  2. Select the desired event.
  3. Activate the workflow – n8n registers the webhook automatically.
  4. When you deactivate the workflow, the webhook is automatically removed.

Example Workflows

1. Automated Content Quality Check

Automatically check texts from external systems (e.g. CMS, forms) for non-preferred terminology and trigger a notification if needed.

Structure: Webhook Trigger → Text preparation → Lexeri (Check Terminology) → IF Node (has_forbidden_terms?) → Slack message / Email

2. Termbase Synchronization

Keep your terminology database up to date with regular imports from a central glossary file.

Structure: Schedule Trigger → HTTP Request (fetch file) → Lexeri (Import Terms) → Slack (report import status)

3. Automatic Term Extraction from New Documents

Automatically start a term extraction job when a document is uploaded and create a review job.

Structure: Google Drive / Dropbox Trigger → Lexeri (Extract Terms) → Lexeri (Create Term Request) → Email to terminology manager

4. Real-Time Notifications for New Terms

Automatically notify your translation team when new terms are added to the terminology database.

Structure: Lexeri Trigger (Term Created) → Message formatting → Slack / Email → Airtable / Notion (log term)

5. API-Based Term Lookup

Automatically respond to incoming term search queries from external systems.

Structure: Webhook → Lexeri (Search Terms) → Format result → Webhook response

Frequently Asked Questions

The node does not appear in the library after installation. Make sure n8n has been fully restarted. For Docker instances, run docker compose restart. Also verify that the installation completed without errors (Settings → Community Nodes).

The credential test fails. Check that the API token was copied correctly (no leading or trailing whitespace). Also verify that the base URL matches your Lexeri instance (production or sandbox).

The import runs asynchronously – how do I check the status? Save the identifier from the import response and query the status via the Lexeri API or directly in the Lexeri interface.

Can I manage multiple termbases with a single node instance? Each API token is tied to a specific termbase. For multiple termbases, create separate credentials with the respective token.

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